WO2016002776A1 - Appareil de surveillance - Google Patents

Appareil de surveillance Download PDF

Info

Publication number
WO2016002776A1
WO2016002776A1 PCT/JP2015/068816 JP2015068816W WO2016002776A1 WO 2016002776 A1 WO2016002776 A1 WO 2016002776A1 JP 2015068816 W JP2015068816 W JP 2015068816W WO 2016002776 A1 WO2016002776 A1 WO 2016002776A1
Authority
WO
WIPO (PCT)
Prior art keywords
distance
intensity
peak point
difference
change
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/JP2015/068816
Other languages
English (en)
Japanese (ja)
Inventor
健一 新房
康伸 大森
三輪　祥太郎
勝治 今城
秀伸 辻
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Mitsubishi Electric Corp
Original Assignee
Mitsubishi Electric Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Mitsubishi Electric Corp filed Critical Mitsubishi Electric Corp
Priority to JP2016531393A priority Critical patent/JP6309099B2/ja
Publication of WO2016002776A1 publication Critical patent/WO2016002776A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V8/00—Prospecting or detecting by optical means
    • G01V8/10—Detecting, e.g. by using light barriers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V8/00—Prospecting or detecting by optical means
    • G01V8/10—Detecting, e.g. by using light barriers
    • G01V8/12—Detecting, e.g. by using light barriers using one transmitter and one receiver
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/181—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using active radiation detection systems
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems

Definitions

  • the present invention relates to a monitoring device that recognizes an object existing in a monitoring area.
  • Patent Document 1 has a problem that accuracy for monitoring a three-dimensional monitoring region is inferior in two-dimensional data obtained from a camera image.
  • a luminance background difference is effectively obtained, but when there is no luminance difference between the object and the background, the object can be accurately recognized.
  • the object can be accurately recognized.
  • there is a sufficient luminance difference between the object and the background but when the object moves in the Z-axis direction on the three-dimensional coordinate (goes straight toward the imaging means such as a camera), the two-dimensional coordinate It is recognized that the object is stationary, and it is difficult to recognize the object as a report target.
  • the present invention has been made to solve the above-described problems.
  • the object of the present invention is to provide a monitoring device capable of accurately recognizing an object.
  • the monitoring device acquires the distance information to the monitoring area from the measurement result of the three-dimensional laser scanner that measured the monitoring area, and sets the current data calculation unit as the current distance data, and the measurement result to the monitoring area.
  • the difference value between the comparison data calculation unit that acquires distance information and converts it into comparison distance data, the current distance data acquired by the current data calculation unit, and the comparison distance data converted by the comparison data calculation unit is calculated, and the difference
  • a first change area extraction unit that extracts an area having a value equal to or greater than a threshold value as a change area;
  • the object can be accurately recognized even when there is no sufficient luminance difference between the object and the background, or even when the object moves on the three-dimensional coordinates.
  • FIG. 1 is a block diagram illustrating a configuration of a monitoring device according to Embodiment 1.
  • FIG. It is a figure which shows the structure of a three-dimensional laser scanner. It is explanatory drawing which shows the dispersion mechanism of a three-dimensional laser scanner.
  • 3 is a flowchart showing an operation of the monitoring apparatus according to the first embodiment.
  • 4 is a flowchart illustrating a determination process of a recognition processing unit of the monitoring apparatus according to the first embodiment.
  • FIG. 6 is a block diagram illustrating a configuration of a monitoring device according to a second embodiment.
  • 10 is a flowchart showing the operation of the monitoring apparatus according to the second embodiment.
  • FIG. 10 is a block diagram illustrating a configuration of a monitoring device according to a third embodiment.
  • FIG. 10 is a diagram illustrating an example of processing of a distance calculation unit of a monitoring device according to Embodiment 3. It is a figure which shows extraction of the change area
  • FIG. 10 is a flowchart showing the operation of the monitoring apparatus according to the third embodiment. 10 is a flowchart illustrating a determination process of a recognition processing unit of the monitoring apparatus according to the third embodiment.
  • FIG. 10 is a block diagram illustrating a configuration of a monitoring device according to a fourth embodiment. 10 is a flowchart showing the operation of the monitoring apparatus according to the fourth embodiment.
  • FIG. 10 is a block diagram illustrating a configuration of a monitoring device according to a fifth embodiment.
  • FIG. 10 is a flowchart showing the operation of the monitoring apparatus according to the fifth embodiment.
  • FIG. 10 is a block diagram illustrating a configuration of a monitoring device according to a sixth embodiment. It is a figure which shows the process of the stability confirmation part of the monitoring apparatus which concerns on Embodiment 6.
  • FIG. 14 is a flowchart illustrating the operation of the monitoring apparatus according to the sixth embodiment.
  • 18 is a flowchart illustrating a determination process of a recognition processing unit of the monitoring apparatus according to the sixth embodiment.
  • FIG. 10 is a block diagram illustrating a configuration of a monitoring device according to a seventh embodiment. 18 is a flowchart showing the operation of the monitoring apparatus according to the seventh embodiment.
  • FIG. 20 is a block diagram illustrating a configuration of a monitoring device according to an eighth embodiment. 20 is a flowchart showing the operation of the monitoring apparatus according to the eighth embodiment.
  • FIG. 1 is a block diagram illustrating a configuration of the monitoring apparatus according to the first embodiment.
  • the monitoring apparatus 100 includes a three-dimensional laser scanner 10, a current data calculation unit 20, a current data storage unit 21, a comparison data calculation unit 30, a comparison data storage unit 31, a first change area extraction unit 40, a recognition processing unit 50, and a notification.
  • the processing unit 60 is configured.
  • a background 200 indicating a scanning range of the three-dimensional laser scanner 10 and an object 201 standing in front of the background 200 are shown outside the monitoring apparatus 100.
  • FIG. 2 is a diagram showing the configuration of the three-dimensional laser scanner.
  • the three-dimensional laser scanner 10 includes a laser light emitting unit 11, a dispersion mechanism 13 using a rotating mirror, and a laser light receiving unit 16, and scans the range indicated by the background 200 to obtain distance data and intensity. Get the data.
  • the laser light emitting unit 11 irradiates a laser light pulse 12.
  • the dispersion mechanism 13 is a mechanism that disperses the laser light pulse 12 emitted from the laser light emitting unit 11 in a wide angle range.
  • a dispersion mechanism 13 using a rotating mirror is shown. Details of the dispersion mechanism 13 using the rotating mirror will be described later.
  • the dispersed laser light pulse 14 dispersed by the dispersion mechanism 13 is irradiated and reflected on the background 200 or an object (not shown in FIG. 2) to form a laser reflected light 15.
  • the dispersion laser light pulse 14 is sequentially dispersedly irradiated in the X direction and the Y direction of the background 200. Specifically, 6 points in the X direction of the background 200 and 2 points in the Y direction of the background 200 are distributedly irradiated to a total of 12 points.
  • the laser light receiving unit 16 receives the laser reflected light 15 reflected by the reflection target, calculates the distance to the reflection target based on the time difference from light emission to light reception, and sets it as distance data.
  • the distance is calculated individually for all irradiation positions distributed in a total of 12 points, 6 points in the X direction of the background 200 and 2 points in the Y direction of the background 200.
  • the laser light receiving unit 16 calculates the reflectance at each point of the reflection target based on the ratio of the irradiated light amount and the received light amount with respect to all the dispersed irradiation positions, and sets it as intensity data.
  • the distance data and intensity data 17 calculated by the laser receiving unit 16 are output to the current data calculation unit 20 and the comparison data calculation unit 30 shown in FIG.
  • the dispersion mechanism 13 using a rotating mirror is used, but other dispersion mechanisms may be applied.
  • a scanless optical system that scans a mirror without a motor may be used.
  • the dispersion mechanism 13 includes a first rotating mirror 13a, a first motor 13b, a second rotating mirror 13c, and a second motor 13d.
  • the first rotating mirror 13a operates in synchronization with the pulse frequency of the incident laser light pulse 12, and disperses the laser light pulse 12 in the horizontal direction with respect to the surface of the first rotating mirror 13a. Horizontally dispersed laser light pulses 13e dispersed in the horizontal direction are always dispersed at the same angle.
  • the first motor 13b is a drive source that drives the first rotating mirror 13a.
  • the second rotating mirror 13c operates in synchronization with the pulse frequency of the incident laser light pulse 12, and further disperses the horizontal dispersion laser light pulse 13e in the vertical direction.
  • the vertically dispersed laser light pulses 13f dispersed in the vertical direction are always dispersed at the same angle.
  • the second motor 13d is a drive source that drives the second rotating mirror 13c.
  • the three-dimensional laser scanner 10 obtains the following three-dimensional information of X, Y, and Z.
  • X horizontal coordinate (6 points in the example of FIG. 2)
  • Y vertical coordinate (2 points in the example of FIG. 2)
  • Z Distance data (depth information in the Z-axis direction (hereinafter referred to as Z-axis information)) Since the three-dimensional information includes the Z-axis information, the amount of movement in the Z-axis direction can be determined even when the object moves in the Z-axis on the three-dimensional coordinates (goes straight toward the three-dimensional laser scanner 10). To obtain the difference.
  • the current data calculation unit 20 acquires the distance data input from the three-dimensional laser scanner 10 and stores the current distance data of the monitoring area in the current data storage unit 21 as the current data.
  • the current data calculation unit 20 often stores the input distance data itself in the current data storage unit 21.
  • the comparison data calculation unit 30 acquires distance data input from the three-dimensional laser scanner 10, converts it into comparison data, and stores it in the comparison data storage unit 31.
  • the conversion processing to the comparison data is performed by obtaining the average distance data from the distance data for the past 50 frames from the input distance data and using it as comparison data, or the distance data of the frame immediately before the input distance data. Obtained as comparison data.
  • the first change area extraction unit 40 acquires the current data stored in the current data storage unit 21 and the comparison data stored in the comparison data storage unit 31, and compares the current data and the comparison data in units of pixels. Then, a difference value is calculated, and a pixel area whose calculated difference value is equal to or larger than a preset threshold value is extracted as a change area. Generally, a fixed threshold value is set, and converted into binary data depending on whether or not the difference value is greater than or equal to the set threshold value.
  • the recognition processing unit 50 recognizes whether or not the change area is a notification target based on whether or not the condition of the change area extracted by the first change area extraction unit 40 satisfies a predetermined condition. Do.
  • the notification processing unit 60 performs notification processing based on the recognition result of the recognition processing unit 50. Examples of the notification process include a process of transmitting a specific signal to a higher-level PC or the like, or a process of sounding a buzzer of the apparatus.
  • FIG. 4 is a flowchart showing the operation of the monitoring apparatus according to the first embodiment.
  • the three-dimensional laser scanner 10 scans the range of the background 200 (step ST1), and acquires distance data and intensity data (step ST2).
  • the range of the background 200 is divided into 80 ⁇ 60, which is the resolution of the three-dimensional laser scanner 10, and scanned.
  • the distance data is generally digital data, and here, multi-value data of 8 bits per pixel of 80 ⁇ 60 pixels is used.
  • the current data calculation unit 20 accumulates the 80 ⁇ 60 pixel distance data acquired in step ST2 in the current data accumulation unit 21 as current data (step ST3).
  • the comparison data calculation unit 30 converts the distance data of 80 ⁇ 60 pixels acquired in step T2 into comparison data and stores it in the comparison data storage unit 31 (step ST4).
  • the first change area extraction unit 40 calculates a difference value for each pixel by using the current data stored in the current data storage unit 21 and the comparison data stored in the comparison data storage unit 31 (step ST5). ).
  • the obtained difference value indicates “distance difference”.
  • the obtained difference value indicates “distance between the background and the object”.
  • the first change area extraction unit 40 determines whether or not the obtained difference value is equal to or greater than a preset threshold value (step ST6). . If the difference value is greater than or equal to the threshold value (step ST6; YES), the pixel area is extracted as a change area (step ST7). On the other hand, if the difference value is less than the threshold value (step ST6; NO), it is determined that the pixel area is not a change area (step ST8), and the process proceeds to step ST9. Thereafter, the first change area extraction unit 40 determines whether or not processing has been performed for all 80 ⁇ 60 pixels (step ST9). When the process is not performed for all 80 ⁇ 60 pixels (step ST9; NO), the process returns to step ST5 and the above-described process is repeated.
  • step ST9; YES when processing has been performed for all 80 ⁇ 60 pixels (step ST9; YES), the recognition processing unit 50 determines whether or not the change region extracted in step ST7 satisfies the matching condition (step ST10). If the verification condition is satisfied (step ST10; YES), the change area is recognized as a notification target (step ST11). On the other hand, when the verification condition is not satisfied (step ST10; NO), it is determined that the change area is not a notification target (step ST12), and the process returns to step ST1.
  • the notification processing unit 60 performs notification processing on the notification target recognized in step ST11 (step ST13), and returns to the processing of step ST1.
  • FIG. 5 is a flowchart illustrating a determination process of the recognition processing unit of the monitoring apparatus according to the first embodiment.
  • the recognition processing unit 50 determines whether or not the change area exists within the monitoring range (step ST21). When it exists in the monitoring range (step ST21; YES), it is further determined whether or not the change area has a predetermined area (step ST22). When it has a predetermined area (step ST22; YES), it is further determined whether or not the change area has a predetermined vertical and horizontal dimension (step ST23). If it has predetermined vertical and horizontal dimensions (step ST23; YES), it is further determined whether or not the change area has a predetermined moving speed (step ST24). When it has a predetermined moving speed (step ST24; YES), it progresses to step ST11 and it recognizes that a change area
  • step ST21; NO does not exist within the monitoring range
  • step ST22; NO does not have a predetermined area
  • step ST23; NO does not have a predetermined vertical / horizontal dimension
  • step ST24; NO when it does not have a predetermined movement speed
  • the current data calculation unit 20 that acquires current data from the distance data acquired by the three-dimensional laser scanner 10 and the distance data acquired by the three-dimensional laser scanner 10 are used. Since it comprised so that the comparison data calculating part 30 which acquires comparison data, and the 1st change area extraction part 40 which extracts a change area from the difference value of present data and comparison data may be provided as a difference value Information on the distance to the background can be obtained, and the difference between the object and the background can be recognized even when there is no sufficient luminance difference between the object and the background. Further, by using the Z-axis information included in the distance information acquired by the three-dimensional laser scanner 10, it is possible to recognize the movement of the object in the Z-axis direction on the three-dimensional coordinates. As a result, the recognition accuracy of the object can be improved.
  • FIG. FIG. 6 is a block diagram illustrating a configuration of the monitoring apparatus according to the second embodiment.
  • the monitoring device 100a according to the second embodiment is provided with a positive / negative map matching unit 41 in addition to the first change region extraction unit 40 of the monitoring device 100 according to the first embodiment shown in FIG.
  • the same or corresponding parts as those of the monitoring apparatus 100 according to the first embodiment are denoted by the same reference numerals as those used in the first embodiment, and the description thereof is omitted or simplified.
  • the first change area extraction unit 40 acquires the current data stored in the current data storage unit 21 and the comparison data stored in the comparison data storage unit 31 and compares them with the current data.
  • the difference value is calculated by comparing the data with the pixel unit.
  • the positive / negative map collating unit 41 refers to whether the difference value calculated by the first change region extracting unit 40 is a positive value or a negative value, and collates with map data set in advance.
  • the sign of the difference value is based on the distance relationship between the background 200 and the object 201. When the object 201 is in front of the background 200, the difference value is “positive” and the background 200 is the object 201. If it is in front, the difference value is “negative”.
  • the background 200 is a solid shield such as a wall
  • the object 201 always passes through the front side of the wall.
  • An object passing through the back side of the wall cannot be visually recognized and is not scanned by the three-dimensional laser scanner 10.
  • the background 200 is, for example, a net fence
  • the object 201 is scanned by the three-dimensional laser scanner 10 that can be visually recognized regardless of whether the object 201 exists on the front side or the back side of the fence.
  • the positive / negative map collation unit 41 stores in advance conditions for limiting the difference value as map data, collates the map data with the difference value, and corrects the difference value rejected by the map data condition.
  • the condition of the map data is “only the positive value of the pixel difference value of the pixel (x, y) is allowed”. Become. Under this condition, when a negative value is calculated as the difference value of the pixel (x, y), the pixel is regarded as noise, and the difference value is forcibly corrected to “0”. This eliminates a difference value that does not occur depending on the conditions of the background 200, and improves the accuracy of the calculated difference value.
  • the first change region extraction unit 40 determines whether or not the difference value collated by the positive / negative map collation unit 41 is equal to or greater than a preset threshold value, and extracts a pixel region that is equal to or greater than the threshold value as a change region.
  • FIG. 7 is a flowchart showing the operation of the monitoring apparatus according to the second embodiment.
  • the same steps as those of the monitoring apparatus 100 according to the first embodiment are denoted by the same reference numerals as those used in FIG. 4, and the description thereof is omitted or simplified.
  • step ST5 when the first change area extraction unit 40 calculates the difference value for each pixel using the current data stored in the current data storage unit 21 and the comparison data stored in the comparison data storage unit 31.
  • the positive / negative map collating unit 41 collates the calculated difference value with the map data (step ST31), and determines whether or not the map data is rejected (step ST32).
  • step ST32 If the map data condition is rejected (step ST32; YES), the positive / negative map matching unit 41 corrects the value of the difference value (step ST33). On the other hand, if it is not rejected by the map data condition (step ST32; NO), the process proceeds to step ST6.
  • the first change region extraction unit 40 determines whether or not the difference value obtained in step ST5 or step ST33 is greater than or equal to a preset threshold value (step ST6). Thereafter, the flowchart performs the processing from step ST7 to step ST13 described above.
  • the difference value calculated by the first change region extraction unit 40 is collated with the map data in which the condition is set in advance, and the map data condition is rejected. Therefore, the difference value that cannot be generated depending on the background condition can be eliminated, and the accuracy of the calculated difference value can be improved. Thereby, the recognition accuracy of the object can be improved.
  • FIG. 8 is a block diagram illustrating a configuration of the monitoring apparatus according to the third embodiment.
  • the monitoring apparatus 100b according to the third embodiment includes a three-dimensional laser scanner 10, a distance histogram creation unit 71, an object distance peak point calculation unit 72, a background distance peak point calculation unit 73, and a distance difference calculation unit 74.
  • the background 200 indicating the scan range of the three-dimensional laser scanner 10 the object 201 standing in front of the background 200, and the diffusion region 202 of the laser light pulse 12 are illustrated outside the monitoring apparatus 100 b.
  • the purpose of the monitoring apparatus 100b is to recognize and notify the object 201.
  • the three-dimensional laser scanner 10 includes the laser light emitting unit 11, the dispersion mechanism 13, and the laser light receiving unit 16 shown in FIG. 2 as in the first embodiment, and scans the range indicated by the background 200 to obtain distance data and intensity data. To get.
  • the laser light pulse 12 emitted from the three-dimensional laser scanner 10 divides the field of view into areas corresponding to the resolution of the three-dimensional laser scanner 10 and irradiates one pulse to the divided area.
  • the laser light pulse 12 has a characteristic of diffusing, and when the background 200 shown in FIG. 8 is, for example, a flat wall, the laser light pulse 12 diffuses into the diffusion region 202 on the wall surface.
  • the diffusion region 202 indicates the diffusion range of the laser light pulse 12, and the diffusion range is determined by the distance from the three-dimensional laser scanner 10 to the background 200. For example, when the distance from the three-dimensional laser scanner 10 to the background 200 is 100 m, the diameter 202a of the diffusion region 202 is 30 cm.
  • the laser light pulse 12 diffused in the diffusion region 202 is reflected by the background 200 or the object 201 and enters the three-dimensional laser scanner 10 as the laser reflected light 15.
  • the three-dimensional laser scanner 10 calculates the distance and reflectance to the background 200 or the object 201 based on the received laser reflected light 15, and acquires distance data and intensity data.
  • the acquired distance data is output to the distance histogram creation unit 71.
  • the distance histogram creation unit 71 creates a distance histogram for each pixel based on the distance data input from the three-dimensional laser scanner 10. More specifically, the distance histogram creation unit 71 creates a first distance histogram for the pixel (x, y) based on the distance data for the past 10 scans of the three-dimensional laser scanner 10. The first distance histogram is created for all pixels. Further, a second distance histogram at the pixel (x, y) is created based on distance data for the past 50 scans of the three-dimensional laser scanner 10. The creation of the second distance histogram is performed for all pixels.
  • FIG. 9 is a diagram illustrating an example of the process of the distance calculation unit of the monitoring apparatus according to the third embodiment
  • FIG. 9A illustrates an example of the distance histogram created by the distance histogram creation unit 71.
  • the horizontal axis indicates the distance (m)
  • the vertical axis indicates the frequency.
  • the distance histogram of the pixel (x, y) shown in FIG. 9A is a distance histogram of coordinates where the background 200 that is 100 m away from the three-dimensional laser scanner 10 and the object 201 overlap the near side of the background 200.
  • a high frequency in the vicinity of the distance of 100 m indicates a wall that is the background 200
  • a high frequency in the vicinity of the distance of 30 m indicates the object 201
  • the other distributions are errors due to distance jitter.
  • the pixel (x, y) described above is a coordinate at which the object 201 overlaps the near side of the background 200, and the background 200 and the object 201 are both irradiated with the laser light pulse 12.
  • the distance data that is the calculation result of the three-dimensional laser scanner 10 fluctuates to the distance of the background 200 when the ratio of the background 200 is high, and fluctuates the distance of the object 201 when the ratio of the object 201 is high.
  • These distance fluctuations are distance jitter.
  • the configuration of the third embodiment Is applied to suppress errors due to distance jitter and improve the extraction accuracy of the change region.
  • the object distance peak point calculation unit 72 calculates a peak point by smoothing the first distance histogram created by the distance histogram creation unit 71.
  • FIG. 9B is a diagram illustrating calculation of the object distance peak point at the pixel (x, y).
  • the average of the frequencies at the distance P ⁇ 10 is calculated for the frequency at a certain distance P and replaced with the frequency at the distance P (processing 1a). This replacement process is performed for all distances 0 m to 150 m in the distance histogram. If the replaced frequencies are connected by a line, a gentle curve is obtained (Process 2a).
  • the slope of the obtained curve is measured from a position at a distance of 0 m, and the point at which the slope changes from a right-up slope to a right-down slope is calculated as a peak point (processing 3a, arrows a and b in FIG. 9B) , C).
  • This peak point calculation process is performed up to a distance of 150 m (process 4a).
  • the obtained peak point becomes the target object distance peak point.
  • a plurality of peak points are calculated. For example, when three or more peak points are calculated, processing for reducing the peak points is performed. As processing for reducing the peak points, the above-described processing 1a to processing 4a are repeated until the peak points converge to about three. Thereby, a histogram curve including about three peak points is obtained. The peak point existing in the histogram curve is the target object distance peak point.
  • FIG. 9C is a diagram showing calculation of the background distance peak point at the pixel (x, y).
  • the average of the frequency of the distance P ⁇ 10 is calculated with respect to the frequency at a certain distance P and replaced with the frequency of the distance P (processing 1b). This replacement process is performed for all distances from 0 m to 150 m in the histogram. If the replaced frequencies are connected by a line, a gentle curve is obtained (Process 2b).
  • the slope of the obtained curve is measured from a position at a distance of 0 m, and a point at which the slope moves from a right-up slope to a right-down slope is calculated as a peak point (processing 3b).
  • This peak point calculation process is performed up to a distance of 150 m (process 4b).
  • the obtained peak point becomes the target background distance peak point.
  • a plurality of peak points are calculated. For example, when two or more peak points are calculated, processing for reducing the peak points is performed. As processing for reducing the peak points, the above-described processing 1b to processing 4b are repeated until the peak points converge to one. As a result, a histogram curve including one peak point is obtained. The peak point existing in the histogram curve is the target background distance peak point.
  • the difference between the first distance histogram and the second distance histogram is the time required to create the histogram.
  • the first distance histogram is created based on the distance data for the past 10 scans of the three-dimensional laser scanner 10
  • the second distance histogram is the distance data for the past 50 scans of the three-dimensional laser scanner 10. Create based on.
  • the second distance histogram uses five times as much time as the first distance histogram, and the second distance histogram is insensitive to short-time changes compared to the first distance histogram. (Indicating a long-term change in the monitoring area) and a histogram that is strongly influenced by the distance of the fixed background.
  • the first distance histogram is sensitive to a short-time change (indicating a short-time change in the monitoring area) and is a histogram that is strongly influenced by the distance of the object.
  • the object distance peak point and the background distance peak point are calculated.
  • the distance difference calculation unit 74 calculates a difference from a histogram curve including an object distance peak point (hereinafter referred to as an object distance histogram curve) and a histogram curve including a background distance peak point (hereinafter referred to as a background distance histogram curve). Calculate the peak point.
  • FIG. 9D is a diagram illustrating difference peak point calculation at the pixel (x, y). As a specific calculation method, first, the background distance histogram curve shown in FIG. 9C is regarded as a normal distribution curve, and the standard deviation (distance from the mean ⁇ to the inflection point) ⁇ of the normal distribution is used.
  • a range 3 ⁇ a centering on the background distance peak point C (average ⁇ in the normal distribution) is determined (processing 1c). Then, the subject distance histogram curve, deletes the peak point located in the range 3 [sigma] a (processing 2c). The histogram 2 shown in FIG. 9D is obtained by the process 2c. The maximum peak point included in the obtained histogram curve is calculated as the difference peak point D (processing 3c). Finally, the histogram including the difference peak point D is regarded as a normal distribution curve, the range 3 ⁇ b centering on the difference peak point D is determined, and the position of the difference peak point D and the position of the range 3 ⁇ b are stored (processing 4c). ).
  • FIG. 10 is a diagram illustrating extraction of a change region of the monitoring apparatus according to the third embodiment.
  • FIG. 10A and FIG. 10B are explanatory views showing creation of an integrated region by the distance difference connection processing unit
  • FIG. 10A is a diagram in which the object 201 is arranged on the background 200
  • FIG. 10C is a diagram illustrating the change region extracted by the second change region extraction unit.
  • the distance difference connection processing unit 75 connects the distance information indicated by the difference peak points of all the pixels calculated by the distance difference calculation unit 74 to create an integrated region. For example, when the difference peak point is calculated for each pixel of 80 ⁇ 60 pixels, the distance difference connection processing unit 75 places the distance information indicated by the difference peak point in the virtually created 80 ⁇ 60 pixel cell. To create an integrated area. As shown in FIGS. 10 (a) and 10 (b), the disposition of distance information is, for example, a pixel where a difference peak point exists is colored gray, and a pixel where no difference peak point exists is colored white. Make visual arrangements. In FIG. 10A, the position where the object 201 exists and the pixel position of the integrated region 203 coincide. Note that the coloring of the pixels is not limited to gray and can be changed as appropriate.
  • the position of the difference peak point calculated by the distance difference calculation unit 74 and the position of the range 3 ⁇ it is similar to at least 3 pixels among the surrounding 8 pixels centered on a certain pixel (x, y) It is determined whether or not there is a difference peak point. Whether there is a similar difference peak point is determined by whether another difference peak point exists in the range 3 ⁇ around the difference peak point of a certain pixel (x, y). This process is performed for all pixels.
  • FIG. 10C shows the change region 204 after the filter processing by the second change region extraction unit 42.
  • the recognition processing unit 50 determines that the change area is a notification target based on whether or not the condition of the change area extracted by the second change area extraction unit 42 satisfies a predetermined condition.
  • the notification processing unit 60 performs notification processing based on the recognition result of the recognition processing unit 50.
  • the notification process is a process of transmitting a specific signal to a higher-level PC or the like, or a process of sounding a buzzer of the apparatus.
  • FIG. 11 is a flowchart showing the operation of the monitoring apparatus according to the third embodiment.
  • the same steps as those of the monitoring apparatus 100 according to the first embodiment are denoted by the same reference numerals as those used in FIG. 4, and the description thereof is omitted or simplified.
  • the case where the resolution of the three-dimensional laser scanner 10 is 80 ⁇ 60 pixels will be described as an example.
  • the three-dimensional laser scanner 10 scans the range of the background 200 (step ST1), and acquires distance data and intensity data (step ST2). Specifically, the range of the background 200 is divided into 80 ⁇ 60, which is the resolution of the three-dimensional laser scanner 10, and scanned.
  • the distance data and the intensity data are generally digital data, and here, multi-value data of 8 bits per pixel of 80 ⁇ 60 pixels is used.
  • the distance histogram creation unit 71 creates a first distance histogram and a second distance histogram based on the distance data acquired in step ST2 (step ST41).
  • the object distance peak point calculation unit 72 calculates an object distance peak point from the first distance histogram created in step ST41 (step ST42), and creates an object distance histogram curve (step ST43).
  • the background distance peak point calculation unit 73 calculates a background distance peak point from the second distance histogram created in step ST41 (step ST44), and creates a background distance histogram curve (step ST45).
  • the distance difference calculation unit 74 calculates a difference peak point between the object distance histogram curve created in step ST43 and the background distance histogram curve created in step ST45 (step ST46).
  • the distance calculation unit 70 determines whether or not the processing from step ST42 to step 46 has been performed for all the pixels (step ST47). If all the pixels have not been processed (step ST47; NO), the process returns to step ST41 and the above-described processing is repeated.
  • the distance difference connection processing unit 75 connects the distance information of the difference peak points of all the pixels obtained in step ST46, and creates an integrated region (step). ST48).
  • the second change area extraction unit 42 performs a filtering process on the integrated area created in step ST48 to extract a change area (step ST49).
  • the recognition processing unit 50 determines whether or not the change area extracted in step ST49 satisfies the verification condition (step ST50). When the verification condition is satisfied (step ST50; YES), the change area is recognized as a notification target (step ST11).
  • step ST50 if the verification condition is not satisfied (step ST50; NO), it is determined that the change area is not a notification target (step ST12), and the process returns to step ST1.
  • the notification processing unit 60 performs notification processing on the notification target recognized in step ST11 (step ST13), and returns to the processing of step ST1.
  • FIG. 12 is a flowchart illustrating the determination process of the recognition processing unit of the monitoring apparatus according to the third embodiment.
  • the recognition processing unit 50 determines whether or not the change area has a predetermined area (step ST51). When it has a predetermined area (step ST51; YES), it is further determined whether or not the change area has a predetermined vertical and horizontal dimension (step ST52). If it has predetermined vertical and horizontal dimensions (step ST52; YES), it is further determined whether or not the change area has a predetermined moving speed (step ST53). If it has a predetermined moving speed (step ST53; YES), it is further determined whether or not the change area has a predetermined existence time (step ST54). When it has the predetermined existence time (step ST54; YES), the process proceeds to step ST11, and the change area is recognized as the notification target.
  • step ST51; NO when it does not have a predetermined area (step ST51; NO), when it does not have a predetermined vertical and horizontal dimension (step ST52; NO), when it does not have a predetermined moving speed (step ST53; NO) ), When it does not have the predetermined existence time (step ST54; NO), the process proceeds to step ST12, and it is determined that the change region is not a notification target.
  • the distance histogram creating unit 71 that creates the distance histogram from the distance data acquired by the three-dimensional laser scanner 10 and the object including the object distance peak point from the distance histogram.
  • An object distance peak point calculation unit 72 that creates a distance histogram curve
  • a background distance peak point calculation unit 73 that creates a background distance histogram curve including a background distance peak point from the distance histogram
  • a difference difference calculation unit 74 that calculates a difference peak point from a curve
  • a distance difference connection processing unit 75 that creates an integrated region using distance information of the difference peak point, and a filter process for the integrated region, and a change region
  • a second change region extraction unit 42 for extracting the background, the object, Distance-difference peak point can be obtained based on the relationship, it is possible to recognize the difference also between the object and the background when a sufficient difference in brightness and the object and the background is not present.
  • the recognition accuracy of the object can be improved.
  • FIG. 13 is a block diagram illustrating a configuration of the monitoring apparatus according to the fourth embodiment.
  • the monitoring device 100c according to the fourth embodiment includes a background distance peak information accumulation unit 76 instead of the background distance peak point calculation unit 73 of the monitoring device 100b according to the third embodiment shown in FIG.
  • the same or corresponding parts as those of the monitoring apparatus 100b according to the third embodiment are denoted by the same reference numerals as those used in the third embodiment, and the description thereof is omitted or simplified.
  • the background 200 indicating the scan range of the three-dimensional laser scanner 10, the object 201 standing in front of the background 200, and the diffusion region 202 of the laser light pulse 12 are illustrated outside the monitoring apparatus 100 c.
  • the distance histogram creation unit 71a creates a distance histogram for each pixel based on the distance data input from the three-dimensional laser scanner 10. However, based on the distance data for the past 10 scans of the three-dimensional laser scanner 10, only the first distance histogram for the pixel (x, y) is created.
  • the background distance peak information accumulating unit 76 stores background distance peak points based on a histogram (corresponding to the second distance histogram shown in the third embodiment described above) that is strongly influenced by the distance to the fixedly existing background 200.
  • the position information and the background distance peak information in which the position information of the range 3 ⁇ a centered on the background distance peak point is fixed in advance are stored.
  • the distance difference calculation unit 74 a acquires the histogram curve including the object distance peak point calculated by the object distance peak point calculation unit 72 (hereinafter referred to as the object distance histogram curve) and the background distance peak information accumulation unit 76.
  • a difference peak point is calculated from the background distance peak information.
  • a histogram curve including a difference peak point by deleting a peak point located in the range 3 ⁇ a which is a fixed value from the object distance histogram curve. See FIGS. 9C and 9D).
  • the maximum peak point included in the obtained histogram curve is calculated as a difference peak point, and a range 3 ⁇ b around the difference peak point is determined (see FIG. 9D).
  • the position of the obtained difference peak point and the position of the range 3 ⁇ b centered on the difference peak point are stored.
  • FIG. 14 is a flowchart showing the operation of the monitoring apparatus according to the fourth embodiment.
  • the distance histogram creation unit 71a creates a first distance histogram based on the distance data acquired in step ST2 (step ST61).
  • the object distance peak point calculation unit 72 calculates an object distance peak point from the first distance histogram created in step ST61 (step ST42), and creates an object distance histogram curve (step ST43).
  • the distance difference calculation unit 74a acquires background distance peak information from the background distance peak information storage unit 76 (step ST62), the object distance histogram curve created in step ST43, and the background distance peak information acquired in step ST62.
  • the difference peak point is calculated from (step ST63).
  • the distance calculation unit 70a determines whether or not the processing from step ST61 to step 63 has been performed for all the pixels (step ST47). When the process is not performed for all the pixels (step ST47; NO), the process returns to step ST61 and the above-described process is repeated. On the other hand, if all pixels have been processed (step ST47; YES), the process proceeds to step ST48.
  • Embodiment 5 In the above-described third embodiment, the configuration in which the change area is extracted based on the distance data of the three-dimensional laser scanner 10 has been described. However, in the fifth embodiment, the change area is determined based on the intensity data of the three-dimensional laser scanner 10. The structure to extract is shown.
  • the resolution of the distance of the laser light pulse 12 has a limit. For example, when the distance resolution of the laser light pulse 12 is 50 cm and the background 200 and the object 201 are at a distance of 50 cm or less, the background 200 and the object 201 cannot be distinguished. This is a problem in distance resolution, which occurs when the object 201 moves along the background 200 such as a wall, and the object 201 cannot be found in distance resolution.
  • the fifth embodiment shows a configuration in which the object 201 that cannot be recognized in terms of distance resolution can be recognized using the intensity data input from the three-dimensional laser scanner 10.
  • FIG. 15 is a block diagram illustrating a configuration of the monitoring apparatus according to the fifth embodiment.
  • the monitoring apparatus 100d according to the fifth embodiment includes a three-dimensional laser scanner 10, an intensity histogram creation unit 81, an object intensity peak point calculation unit 82, a background intensity peak point calculation unit 83, and an intensity difference calculation unit 84.
  • the intensity calculation unit 80, the intensity difference connection processing unit 85, the third change area extraction unit 86, the recognition processing unit 50, and the notification processing unit 60 are included.
  • the background 200 indicating the scan range of the three-dimensional laser scanner 10, the object 201 standing in front of the background 200, and the diffusion region 202 of the laser light pulse 12 are shown outside the monitoring apparatus 100 d.
  • the configuration of the three-dimensional laser scanner 10 is the same as that of the first to fourth embodiments.
  • the intensity histogram creation unit 81 creates an intensity histogram for each pixel based on the intensity data input from the three-dimensional laser scanner 10. More specifically, the intensity histogram creating unit 81 creates a first intensity histogram for the pixel (x, y) based on intensity data for the past 10 scans of the three-dimensional laser scanner 10. The first intensity histogram is created for all pixels. Further, a second intensity histogram for the pixel (x, y) is created based on the intensity data for the past 50 scans, and the second intensity histogram is created for all the pixels.
  • FIG. 16 is a diagram illustrating an example of processing of the intensity calculation unit of the monitoring apparatus according to the fifth embodiment
  • FIG. 16A illustrates an example of a histogram created by the intensity histogram creation unit 81.
  • the horizontal axis indicates intensity (%)
  • the vertical axis indicates frequency.
  • the intensity histogram of the pixel (x, y) shown in FIG. 16A the frequency around the intensity of 20% is high, and the reflectance of the object 201 is reflected. The other frequency is noise.
  • FIG. 16B is a diagram illustrating calculation of the object intensity peak point at the pixel (x, y).
  • the average of the frequencies of the intensity Q ⁇ 10 is calculated for the frequency at a certain intensity Q and replaced with the frequency of the intensity Q (processing 1d). This replacement process is performed for all of the intensity histograms having an intensity of 0% to 100%. If the replaced frequencies are connected by a line, a gentle curve is obtained (Process 2d).
  • a slope is measured from the position where the intensity is 0% with respect to the obtained curve, and a point at which the slope moves from a right-up slope to a right-down slope is calculated as a peak point (Process 3d, arrow d, FIG. 16B). e, f). This peak point calculation process is performed up to the position where the intensity is 100% (process 4d). The obtained peak point becomes the target object strength peak point.
  • a plurality of peak points are calculated. For example, when three or more peak points are calculated, processing for reducing the peak points is performed. As processing for reducing the peak points, the above-described processing 1d to processing 4d are repeated until the peak points converge to about three. Thereby, a histogram curve including about three peak points is obtained. The peak point existing in the histogram curve is the target object intensity peak point.
  • FIG. 16C is a diagram showing calculation of the background intensity peak point at the pixel (x, y).
  • the average of the frequencies of the intensity Q ⁇ 10 is calculated with respect to the frequency at a certain intensity Q and replaced with the frequency of the intensity Q (processing 1e). This replacement process is performed for all the histograms having an intensity of 0% to 100%. When the replaced frequencies are connected with a line, a gentle curve is obtained (Process 2e).
  • the inclination is measured from the position where the intensity is 0% with respect to the obtained curve, and the point at which the slope moves from the upward slope to the downward slope is calculated as a peak point (processing 3e).
  • This peak point calculation process is performed up to the position where the intensity is 100% (process 4e).
  • the obtained peak point becomes the target background intensity peak point.
  • a plurality of peak points are calculated. For example, when two or more peak points are calculated, processing for reducing the peak points is performed. As processing for reducing the peak points, the above-described processing 1e to processing 4e are repeated until the peak points converge to one. As a result, a histogram curve including one peak point is obtained. The peak point existing in the histogram curve is the target background intensity peak point.
  • the difference between the first intensity histogram and the second intensity histogram is the time required to create the histogram.
  • the first intensity histogram is created based on the intensity data for the past 10 scans of the three-dimensional laser scanner 10
  • the second intensity histogram is the intensity data for the past 50 scans of the three-dimensional laser scanner 10. Create based on.
  • the second intensity histogram uses five times as much time as the first intensity histogram, and the second intensity histogram is insensitive to short-time changes compared to the first intensity histogram. (Indicating a long-term change in the monitoring area), and a histogram that is strongly influenced by the intensity of the background that exists fixedly.
  • the first intensity histogram is sensitive to a short-time change (indicating a short-time change in the monitoring area), and is a histogram that is strongly influenced by the intensity of the object.
  • the object intensity peak point and the background intensity peak point are calculated.
  • the intensity difference calculation unit 84 calculates a difference from a histogram curve including an object intensity peak point (hereinafter referred to as an object intensity histogram curve) and a histogram curve including a background intensity peak point (hereinafter referred to as a background intensity histogram curve). Calculate the peak point.
  • FIG. 16D is a diagram illustrating calculation of a difference peak point at the pixel (x, y). As a specific calculation method, first, the background intensity histogram curve shown in FIG. 16C is regarded as a normal distribution curve, and the standard deviation (intensity from the mean ⁇ to the inflection point) ⁇ of the normal distribution is used.
  • a range 3 ⁇ c centered on the intensity peak point F (average ⁇ in the normal distribution) is determined (processing 1f).
  • the peak point located within the range 3 ⁇ c is deleted from the object intensity histogram curve (processing 2f).
  • the histogram 2 shown in FIG. 16D is obtained by the process 2f.
  • the maximum peak point included in the obtained histogram curve is calculated as the difference peak point G (processing 3f).
  • the histogram including the difference peak point G is regarded as a normal distribution curve, the range 3 ⁇ d centered on the difference peak point G is determined, and the position of the difference peak point G and the position of the range 3 ⁇ d are stored (processing 4f). ).
  • FIG. 17 is a diagram illustrating extraction of a change area of the monitoring apparatus according to the fifth embodiment.
  • FIG. 17A and FIG. 17B are explanatory views showing extraction of a change region by the intensity difference connection processing unit and the third change region extraction unit, and
  • FIG. 17A shows the object 201 on the background 200.
  • the arranged diagram and FIG. 17B are diagrams showing only the background 200.
  • the intensity difference connection processing unit 85 connects the intensity information indicated by the difference peak points of all the pixels calculated by the intensity difference calculation unit 84. For example, when a difference peak point is calculated for each pixel of 80 ⁇ 60 pixels, the intensity difference connection processing unit 85 places the intensity information indicated by the difference peak point in a virtually created 80 ⁇ 60 pixel cell. Connect. For example, as shown in FIGS. 17A and 17B, the arrangement of the intensity information is such that a pixel having a difference peak point is colored gray and a pixel having no difference peak point is colored white. And so on.
  • 3rd change area extraction part 86 extracts a change area from the intensity
  • the change area is extracted based on the difference between the pixel where the difference peak point exists and the pixel where the difference peak point does not exist, and in the above-described example, the pixel colored gray based on the difference in pixel coloring is extracted.
  • the gathering area is extracted as a change area. As shown in FIG. 17A, the position where the object 201 exists and the pixel position of the change area 205 coincide.
  • the recognition processing unit 50 recognizes whether or not the change region is a notification target based on whether or not the condition of the change region extracted by the third change region extraction unit 86 satisfies a predetermined condition. .
  • the notification processing unit 60 performs notification processing based on the recognition result of the recognition processing unit 50.
  • the notification process is a process of transmitting a specific signal to a higher-level PC or the like, or a process of sounding a buzzer of the apparatus.
  • FIG. 18 is a flowchart showing the operation of the monitoring apparatus according to the fifth embodiment.
  • the same steps as those of the monitoring device 100b according to the third embodiment are denoted by the same reference numerals as those used in FIG. 11, and the description thereof is omitted or simplified.
  • the case where the resolution of the three-dimensional laser scanner 10 is 80 ⁇ 60 pixels will be described as an example.
  • the intensity histogram creation unit 81 creates a first intensity histogram and a second intensity histogram based on the intensity data acquired in step ST2 (step ST71).
  • the object intensity peak point calculation unit 82 calculates an object intensity peak point from the first intensity histogram created in step ST71 (step ST72), and creates an object intensity histogram curve (step ST73).
  • the background intensity peak point calculation unit 83 calculates a peak point from the second intensity histogram created in step ST72 (step ST74), and creates a background intensity histogram curve (step ST75).
  • the intensity difference calculation unit 84 calculates a difference peak point between the object intensity histogram curve created in step ST73 and the background intensity histogram curve created in step ST75 (step ST76).
  • the intensity calculation unit 80 determines whether or not the processing from step ST71 to step ST76 has been performed for all pixels (step ST77). If the process has not been performed for all pixels (step ST77; NO), the process returns to step ST71 and the above-described process is repeated.
  • the intensity difference connection processing unit 85 connects the intensity information of the difference peak points of all the pixels obtained in step ST76 (step ST78).
  • the change area extraction unit 86 extracts a change area from the connected intensity information (step ST79).
  • the recognition processing unit 50 determines whether or not the change area extracted in step ST79 satisfies the matching condition (step ST80). If the verification condition is satisfied (step ST80; YES), the change area is recognized as a notification target (step ST11). On the other hand, when the verification condition is not satisfied (step ST80; NO), it is determined that the change area is not a notification target (step ST12), and the process returns to step ST1.
  • the notification processing unit 60 performs notification processing on the notification target recognized in step ST11 (step ST13), and returns to the processing of step ST1.
  • the intensity histogram creating unit 81 that creates the intensity histogram from the intensity data acquired by the three-dimensional laser scanner 10 and the object including the object intensity peak point from the intensity histogram.
  • An object intensity peak point calculation unit 82 that creates an intensity histogram curve, a background intensity peak point calculation unit 83 that creates a background intensity histogram curve including a background intensity peak point from the intensity histogram, an object intensity histogram curve, and a background intensity histogram
  • An intensity difference calculation unit 84 that calculates a difference peak point from the curve, an intensity difference connection processing unit 85 that connects intensity information of the difference peak points, and a third change area extraction that extracts a change area from the connected intensity information Difference peak based on the intensity relationship between the background and the object.
  • FIG. 19 is a block diagram illustrating a configuration of the monitoring apparatus according to the sixth embodiment.
  • the monitoring apparatus 100e of the sixth embodiment is provided with a stability confirmation unit 43 in addition to the monitoring apparatus 100d of the fifth embodiment shown in FIG.
  • the same or corresponding parts as those of the monitoring apparatus 100d according to the fifth embodiment are denoted by the same reference numerals as those used in the fifth embodiment, and description thereof is omitted or simplified.
  • an object 201 standing in front of the background 200, and a diffusion region 202 of the laser light pulse 12 are illustrated outside the monitoring device 100 e.
  • the stability confirmation unit 43 temporarily accumulates the change area extracted by the third change area extraction unit 86 in the accumulation unit 43a.
  • the stability confirmation unit 43 refers to the change region stored in the storage unit 43a, compares the change regions before and after a predetermined time, and determines whether the area change of the change region is equal to or greater than a threshold value. If the area change of the change area is equal to or greater than the threshold value, it is determined that the change area is a person. On the other hand, when the area change of the change area is less than the threshold, it is determined that the change area is other than a person, for example, a signboard, a wall stain, a wall wet, a poster, or the like.
  • the recognition processing unit 50 performs a recognition process as to whether or not only a change area determined to be a person by the stability confirmation unit 43 is a notification target.
  • FIG. 20 is an explanatory diagram illustrating processing of the stability confirmation unit of the monitoring apparatus according to the sixth embodiment.
  • 20 (a), (b), and (c) show a change area when the person 206 is positioned in front of the background 200.
  • FIGS. 20 (d), (e), and (f) show the background 200.
  • the change area when the signboard 207 is positioned in front is shown.
  • the region that is colored gray by the intensity difference connection processing unit 85 and extracted by the third change region extraction unit 86 is a change region.
  • FIG. 20A shows a person 206 and a change area 208 positioned in front of the background 200.
  • FIG. 20B shows only the change region 208 with respect to FIG.
  • FIG. 20C shows a change area 209 after a predetermined time (for example, 1 second) has elapsed since the change area 208 of FIG. 20B was extracted. Since the person 206 moves in the direction of the arrow R, when comparing FIG. 20B and FIG. 20C, the change area 208 corresponding to the person 206 moves in the direction of the arrow R and changes to the change area 209. Yes. In this way, a change area that changes after a predetermined time has elapsed is recognized as a notification target.
  • a predetermined time for example, 1 second
  • FIG. 20D shows the signboard 207 and the change area 210 positioned in front of the background 200.
  • FIG. 20 (e) shows only the change region 210 with respect to FIG. 20 (d).
  • FIG. 20F shows a change area 211 after a predetermined time (for example, 1 second) has elapsed since the change area 210 of FIG. 20E was extracted. Since the signboard 207 does not move, there is no change in the change area 210 and the change area 211 corresponding to the signboard 207 when comparing FIG. 20E and FIG. Thus, it is recognized that a change area that remains in the same place and does not change is not a notification target.
  • a predetermined time for example, 1 second
  • FIG. 21 is a flowchart showing the operation of the monitoring apparatus according to the sixth embodiment.
  • the same steps as those of the monitoring device 100d according to the fifth embodiment are denoted by the same reference numerals as those used in FIG. 18, and the description thereof is omitted or simplified.
  • the stability confirmation unit 43 temporarily stores the extracted change region in the storage unit 43a (step ST81).
  • the stability confirmation unit 43 determines whether or not the change region before and after the lapse of a certain time has been accumulated in the accumulation unit 43a (step ST82). If not accumulated (step ST82; NO), the process returns to step ST1, and the above-described process is repeated.
  • step ST82 when accumulated (step ST82; YES), the stability confirmation unit 43 compares the change regions accumulated in the accumulation unit 43a before and after the elapse of a predetermined time, and determines whether or not the area change of the change region is equal to or greater than a threshold value. Perform (step ST83). If the area change of the change area is equal to or greater than the threshold (step ST83; YES), it is determined that the change area is a person (step ST84), and the recognition processing unit 50 determines whether the change area satisfies the matching condition. Perform (step ST85). If the verification condition is satisfied (step ST85; YES), the change area is recognized as a notification target (step ST11). On the other hand, when the verification condition is not satisfied (step ST85; NO), it is determined that the change area is not a notification target (step ST12), and the process returns to step ST1.
  • step ST83 determines that the change region is other than a person (step ST86), and the process proceeds to step ST12.
  • the notification processing unit 60 performs notification processing on the notification target recognized in step ST11 (step ST13), and returns to the processing of step ST1.
  • FIG. 22 is a flowchart illustrating the determination process of the recognition processing unit of the monitoring apparatus according to the sixth embodiment.
  • the recognition processing unit 50 of the sixth embodiment performs the following processing in which the processing of step ST53 in the flowchart shown in FIG. 12 of the third embodiment is omitted.
  • the recognition processing unit 50 determines whether or not the change area has a predetermined area (step ST51). When it has a predetermined area (step ST51; YES), it is further determined whether or not the change area has a predetermined vertical and horizontal dimension (step ST52).
  • step ST52 If it has predetermined vertical and horizontal dimensions (step ST52; YES), it is further determined whether or not the change area has a predetermined existence time (step ST54). When it has the predetermined existence time (step ST54; YES), the process proceeds to step ST11, and the change area is recognized as the notification target.
  • step ST51; NO when it does not have a predetermined area (step ST51; NO), when it does not have a predetermined vertical and horizontal dimension (step ST52; NO), when it does not have a predetermined existence time (step ST54; NO) ), The process proceeds to step ST12, where it is determined that the change region is not a notification target.
  • a stability confirmation unit that determines whether the change area is a person or not
  • a signboard, a spot on the wall, wetness on the wall, a poster, and the like can be distinguished from a person, and erroneous notification to a person other than the person can be prevented.
  • the configuration in which the three-dimensional laser scanner 10 is arranged in the monitoring devices 100, 100a, 100b, 100c, 100d, and 100e has been described.
  • the distance data and the intensity data may be acquired from the external configuration.
  • FIG. 23 is a block diagram illustrating a configuration of a monitoring device realized by combining the configurations of the first embodiment and the third embodiment.
  • FIG. 24 is a block diagram showing a configuration of a monitoring apparatus realized by combining the configurations of the first embodiment and the fifth embodiment.
  • FIG. 25 is a block diagram showing a configuration of a monitoring device realized by combining the configurations of the third embodiment and the fifth embodiment.
  • FIG. 26 is a block diagram illustrating a configuration of a monitoring device realized by combining the configurations of the first embodiment, the third embodiment, and the fifth embodiment.
  • the second embodiment is applied instead of the first embodiment
  • the fourth embodiment is applied instead of the third embodiment
  • the sixth embodiment is applied instead of the fifth embodiment. It is also possible.
  • Embodiment 7 FIG.
  • the rotating mirror 13a and the rotating mirror 13c always operate in cooperation in a series of operations, and it is necessary to maintain the same relative angle.
  • errors are inherent in physical operations such as driving of the rotating mirror, and errors are also included in the operations of the rotating mirror 13a and the rotating mirror 13c of the dispersion mechanism 13.
  • the position where the incident laser light pulse 12 is finally reflected and arrives is shifted by the error included in the operation of the rotating mirror 13a and the rotating mirror 13c.
  • the laser light pulse 12 that has reached the background is inclined in the vertical and horizontal directions with respect to the ideal arrival position that does not include the error described above.
  • ⁇ 1 point There is a possibility of deviation by ⁇ 1 point. That is, the laser light pulse 12 reaches any one of the 9 points around the ideal arrival position. Therefore, in the seventh embodiment, a configuration is shown in which the surrounding pixels are compared with the current data in addition to the ideal arrival position.
  • FIG. 27 is a block diagram illustrating a configuration of the monitoring apparatus according to the seventh embodiment.
  • the monitoring device 100j according to the seventh embodiment is configured by replacing the first change region extraction unit 40 of the monitoring device 100 according to the first embodiment shown in FIG. 1 with a first change region extraction unit 40a.
  • the same or corresponding parts as those of the monitoring apparatus 100 according to the first embodiment are denoted by the same reference numerals as those used in the first embodiment, and the description thereof is omitted or simplified.
  • the comparison data calculation unit 30 acquires distance data input from the three-dimensional laser scanner 10, converts it into comparison data, and stores it in the comparison data storage unit 31.
  • comparison data for example, distance data of a frame immediately before the input distance data is obtained and used as comparison data.
  • the accumulated distance data is the distance data of points within a range set around the coordinates or pixels. Assuming that the error occurring at the position on the background as described above is “ ⁇ 1 point” and the coordinates of the input distance data are (x, y), the comparison data is centered on the coordinates (x, y). The distance data is set to coordinates moved by ⁇ 1 point in the diagonal direction.
  • the first change area extraction unit 40a acquires the current data accumulated in the current data accumulation unit 21 and all comparison data accumulated in the comparison data accumulation unit 31, and coordinates the current data and all comparison data. Alternatively, a plurality of difference values are calculated by comparison in units of pixels.
  • the first change area extraction unit 40a sets a minimum difference value among the calculated difference values as a true difference value, and extracts a coordinate area or a pixel area in which the true difference value is equal to or greater than a preset threshold as a change area. To do. Generally, a fixed threshold value is set, and converted into binary data depending on whether or not the difference value is greater than or equal to the set threshold value.
  • FIG. 28 is a flowchart showing the operation of the monitoring apparatus according to the seventh embodiment.
  • the same steps as those of the monitoring apparatus 100 according to the first embodiment are denoted by the same reference numerals as those used in FIG. 4, and the description thereof is omitted or simplified.
  • the case where the error occurring at the position on the background is “ ⁇ 1 point” will be described as an example.
  • step ST4 when the comparison data is accumulated in the comparison data accumulation unit 31, the first change area extraction unit 40a acquires the coordinates (x, y) that is the current data accumulated in the current data accumulation unit 21 ( Step ST91). Furthermore, the first change area extraction unit 40a acquires comparison data centered on the coordinates (x, y) of the current data from the comparison data storage unit 31 (step ST92).
  • the first change area extraction unit 40a uses the coordinates (x ⁇ 1, y ⁇ 1), coordinates (x, y ⁇ 1), coordinates (x + 1, y ⁇ 1), coordinates (x -1, y), coordinates (x, y), coordinates (x + 1, y), coordinates (x-1, y + 1), coordinates (x, y + 1), and coordinates (x + 1, y + 1) are acquired.
  • 1st change area extraction part 40a calculates the difference value for every coordinate using the present data acquired by step ST91, and each comparison data acquired by step ST92 (step ST93).
  • the first change area extraction unit 40a sets the smallest difference value among the difference values calculated in step ST93 as a true difference value (step ST94). Since the true difference value obtained in step ST94 is multi-value data of 8 bits, the first change area extraction unit 40a determines whether or not the obtained true difference value is greater than or equal to a preset threshold value. (Step ST95). If the true difference value is greater than or equal to the threshold (step ST95; YES), the pixel area is extracted as a change area (step ST7). On the other hand, when the true difference value is less than the threshold value (step ST95; NO), it is determined that the pixel area is not a change area (step ST8), and the process proceeds to step ST9.
  • the current data of the coordinates (x, y) is vertically and horizontally inclined around the position of the coordinates (x, y). Since it is the distance data of any point within the range of ⁇ 1 point in the direction, even if compared with the comparison data of the same coordinates (x, y) based on the coordinates (x, y) of the current data, the comparison The data is not always correct.
  • step ST93 all the comparison data in the range where the error may occur is prepared for the current data in which an error may occur due to a series of operations of the dispersion mechanism 13, and all the prepared comparison data and the current data The difference value is calculated by comparing the data with the brute force. In the process of step ST93 described above, the nine comparison data prepared and the current data are compared with each other to calculate a difference value.
  • the one having the smallest difference value is finally determined as a true difference value.
  • the current data calculation unit 20 that acquires the current data from the distance data acquired by the three-dimensional laser scanner 10 and the coordinates of the distance data acquired by the three-dimensional laser scanner 10.
  • the comparison data calculating part 30 which acquires the comparison data located in the predetermined range set centering on the pixel, the current data which the current data calculating part 20 acquired, and the several comparison which the comparison data calculating part 30 acquired Since the true difference value is calculated from the difference value with the data, and the first change area extraction unit 40a that extracts the change area from the calculated true difference value is provided, the position where the laser light pulse reaches Even in an environment that includes an error, accurate distance information between the object and the background can be acquired. Thereby, the recognition accuracy of the object can be improved.
  • the seventh embodiment when the point at which the laser light pulse arrives is shifted within a range of ⁇ 1 point in the vertical and horizontal directions around the coordinates of the current data due to an error of the dispersion mechanism 13, for example. Since the difference value is calculated using the nine comparison data around the current data and the true difference value is selected from the difference value, the deviation of the point where the laser light pulse reaches It is possible to select a stable difference value that suppresses the influence of. Thereby, even when the position where the laser light pulse reaches due to an error in distance data is blurred, the influence of the blur can be suppressed to the minimum. Therefore, the recognition accuracy of the object can be improved.
  • the configuration in which the comparison data is acquired from the coordinates located in the range of ⁇ 1 point in the up / down / left / right diagonal direction with the current data as the center has been described.
  • the error occurring at the upper position is not limited to “ ⁇ 1 point”, but varies. Therefore, the range of the comparison data to be acquired varies depending on the error that occurs at the position on the background where the laser light pulse reaches.
  • the structure which acquires comparison data on the basis of a coordinate was shown, it is good also as a structure which acquires comparison data on the basis of a pixel.
  • the case where the first change region extraction unit 40a is applied to the configuration illustrated in the first embodiment has been described.
  • the configuration of the seventh embodiment is illustrated in the second embodiment. It is also applicable to other configurations.
  • the first change region extraction unit 40 shown in FIG. 6 is replaced with the first change region extraction unit 40a described above.
  • the process of step ST5 is replaced with the process of step ST91 to step ST94 described above. The processing after step ST31 is performed on the true difference value acquired at step ST94.
  • Embodiment 8 FIG.
  • the eighth embodiment shows a configuration that improves the extraction sensitivity of the change region when a notification target appears in the field of view.
  • FIG. 29 is a block diagram showing the configuration of the monitoring apparatus according to the eighth embodiment.
  • the monitoring device 100k according to the eighth embodiment additionally includes a determination result accumulation unit 40b in the first change area extraction unit 40a of the monitoring device 100j according to the seventh embodiment shown in FIG.
  • the same or corresponding parts as those of the monitoring apparatus 100j according to the seventh embodiment are denoted by the same reference numerals as those used in the first embodiment, and the description thereof is omitted or simplified.
  • the comparison data calculation unit 30 sets the distance data to be accumulated around the coordinates or pixels of the distance data input from the three-dimensional laser scanner 10.
  • the distance data of the points within the range is converted into comparison data and stored in the comparison data storage unit 31.
  • the determination result accumulation unit 40b is an area for storing past determination results of the first change area extraction unit 40a.
  • the determination result of the first change area extraction unit 40a is a determination result of whether or not the true difference value is greater than or equal to a threshold value. Either a certain coordinate is extracted as a change area or a certain coordinate is not a change area. It is information indicating whether or not it has been determined.
  • the determination result accumulation unit 40b accumulates the determination result at each coordinate or each pixel at least one frame before.
  • the first change area extraction unit 40a acquires the current data accumulated in the current data accumulation unit 21 and all comparison data accumulated in the comparison data accumulation unit 31, and coordinates the current data and all comparison data. Alternatively, a plurality of difference values are calculated by comparison in units of pixels.
  • the first change region extraction unit 40a refers to the determination result storage unit 40b and determines whether the true difference value at the same coordinate one frame before is determined to be equal to or greater than the threshold and is extracted as a change region.
  • the first change area extraction unit 40a acquires the maximum difference value among the difference values calculated at the coordinates as the true difference value.
  • the first change region extraction unit 40a acquires the smallest difference value among the difference values calculated at the coordinates as the true difference value. .
  • the first change area extraction unit 40a extracts, as a change area, a coordinate area or a pixel area whose acquired true difference value is greater than or equal to a preset threshold value.
  • FIG. 30 is a flowchart showing the operation of the monitoring apparatus according to the eighth embodiment.
  • the same steps as those of the monitoring device 100j according to the seventh embodiment are denoted by the same reference numerals as those used in FIG. 28, and the description thereof is omitted or simplified.
  • the case where the error occurring at the position on the background is “ ⁇ 1 point” will be described as an example.
  • the first change area extraction unit 40a refers to the determination result accumulation unit 40b, and the coordinate for which the difference value is calculated in step ST93 changes in the image one frame before. It is determined whether or not the area is determined (step ST101). When it is determined that the region is a change region in the image one frame before (step ST101; YES), the first change region extraction unit 40a sets the maximum difference value among the difference values for each coordinate calculated in step ST93 to be true. (Step ST102). On the other hand, when it is determined that it is not a change area in the image one frame before (step ST101; NO), the first change area extraction unit 40a calculates the minimum difference value among the difference values for each coordinate calculated in step ST93. A true difference value is set (step ST102).
  • the first change area extraction unit 40a determines whether or not the obtained true difference value is equal to or greater than a preset threshold value. A determination is made (step ST95). If the true difference value is greater than or equal to the threshold (step ST95; YES), the pixel area is extracted as a change area (step ST7). On the other hand, when the true difference value is less than the threshold value (step ST95; NO), it is determined that the pixel area is not a change area (step ST8), and the process proceeds to step ST9.
  • the maximum difference value is always selected as the true difference value, and thus the true difference value is always the maximum value. This means that the sensitivity for extracting the change region is high.
  • the minimum difference value is selected as the true difference value. This means that the true difference value is always the minimum value, and the sensitivity for extracting the change region is low.
  • the current data calculation unit 20 that acquires current data from the distance data acquired by the three-dimensional laser scanner 10 and the coordinates of the distance data acquired by the three-dimensional laser scanner 10.
  • it is a determination result of the comparison data calculation unit 30 that acquires comparison data located within a predetermined range set around the pixel and the first change region extraction unit 40a for the image one frame before
  • a determination result storage unit 40b that stores a determination result as to whether or not each coordinate or each pixel of the image before the frame is a change area, and the current data and comparison data positioned within a predetermined range centering on the current data
  • a difference value is calculated, and it is determined whether or not the coordinate for which the difference value has been calculated with reference to the determination result storage unit 40b is a change area in the image one frame before.
  • the maximum difference value is set as the true difference value for the coordinates or pixels that were the change area in the image one frame before. It can be acquired, and the extraction sensitivity of the change area can be improved. Thereby, the detection capability of a report object can be improved and the risk of unreporting can be reduced. Moreover, the recognition accuracy of the object can be improved.
  • the configuration in which the comparison data is acquired from the coordinates located in the range of ⁇ 1 point in the vertical, horizontal, and diagonal directions around the current data has been described.
  • the error occurring at the upper position is not limited to “ ⁇ 1 point”, but varies. Therefore, the range of the comparison data to be acquired varies depending on the error that occurs at the position on the background where the laser light pulse reaches.
  • the structure which acquires comparison data on the basis of a coordinate was shown, it is good also as a structure which acquires comparison data on the basis of a pixel.
  • the configuration of the eighth embodiment is as follows.
  • the present invention can also be applied to the configuration shown in Embodiment Mode 2.
  • the first change region extraction unit 40 shown in FIG. 6 is replaced with the first change region extraction unit 40a and the determination result storage unit 40b described above.
  • the process of step ST5 is replaced with the process of step ST91 to step ST103 described above.
  • the processing after step ST31 is performed on the true difference value acquired at step ST102 or step ST103.
  • Each function of the monitoring device described in the first to eighth embodiments is realized by a processing circuit.
  • the processing circuit can realize the functions described above by hardware, software, firmware, or a combination thereof.
  • Software and firmware are described as programs and stored in a memory.
  • the processing circuit executes the function of each unit by reading and executing the program stored in the memory.
  • the monitoring device can recognize an object with high accuracy, it is suitable for applying to a monitoring camera or the like to accurately recognize a notification target and issue a warning.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Geophysics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Electromagnetism (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Optical Radar Systems And Details Thereof (AREA)
  • Alarm Systems (AREA)
  • Measurement Of Optical Distance (AREA)
  • Burglar Alarm Systems (AREA)

Abstract

　L'invention concerne un appareil de surveillance qui comporte : une unité de calcul de données actuelles (20) pour acquérir des informations relatives à la distance par rapport à une zone surveillée sur la base de résultats de mesure provenant d'un scanner laser tridimensionnel qui a mesuré la zone surveillée, et utiliser ces informations en tant que données de distance actuelles ; une unité de calcul de données de comparaison (30) pour acquérir des informations relatives à la distance par rapport à une zone surveillée sur la base des résultats de mesure, et convertir ces informations en données de distance de comparaison ; et une première unité d'extraction de zone de variation (40) pour calculer une valeur différentielle des données de distance actuelles et des données de distance de comparaison, et extraire, en tant que zone de variation, une zone pour laquelle la valeur différentielle est égale ou supérieure à une valeur de seuil.
PCT/JP2015/068816 2014-07-03 2015-06-30 Appareil de surveillance Ceased WO2016002776A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2016531393A JP6309099B2 (ja) 2014-07-03 2015-06-30 監視装置

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2014137624 2014-07-03
JP2014-137624 2014-07-03

Publications (1)

Publication Number Publication Date
WO2016002776A1 true WO2016002776A1 (fr) 2016-01-07

Family

ID=55019308

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2015/068816 Ceased WO2016002776A1 (fr) 2014-07-03 2015-06-30 Appareil de surveillance

Country Status (2)

Country Link
JP (1) JP6309099B2 (fr)
WO (1) WO2016002776A1 (fr)

Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017195755A1 (fr) * 2016-05-13 2017-11-16 コニカミノルタ株式会社 Système de surveillance
WO2017195754A1 (fr) * 2016-05-13 2017-11-16 コニカミノルタ株式会社 Système de surveillance
WO2017195753A1 (fr) * 2016-05-13 2017-11-16 コニカミノルタ株式会社 Système de surveillance
JP2017227454A (ja) * 2016-06-20 2017-12-28 三菱電機株式会社 監視装置
JP2018067127A (ja) * 2016-10-19 2018-04-26 三菱電機株式会社 監視用画像処理装置および監視装置
JP2018105638A (ja) * 2016-12-22 2018-07-05 三菱電機株式会社 監視装置
JP2019046295A (ja) * 2017-09-05 2019-03-22 三菱電機株式会社 監視装置
JP2019159723A (ja) * 2018-03-12 2019-09-19 株式会社デンソーウェーブ 静止物監視装置
EP3579181A4 (fr) * 2017-02-06 2020-02-12 Mitsubishi Electric Corporation Dispositif de surveillance
JP2020512544A (ja) * 2017-03-01 2020-04-23 アウスター インコーポレイテッド ライダーのための正確な光検出器測定
WO2020090287A1 (fr) * 2018-10-29 2020-05-07 古野電気株式会社 Appareil et procédé de mesure de cible
JP2021004888A (ja) * 2016-12-31 2021-01-14 イノビュージョン アイルランド リミテッドＩｎｎｏｖｕｓｉｏｎ Ｉｒｅｌａｎｄ Ｌｉｍｉｔｅｄ 回転凹面鏡及びビームステアリング装置の組み合わせを用いた、２ｄ走査型高精度ライダー
JP2021113807A (ja) * 2020-01-16 2021-08-05 パイオニア株式会社 反射データ処理装置、反射データ処理方法、およびプログラム
WO2022085310A1 (fr) * 2020-10-20 2022-04-28 ソニーセミコンダクタソリューションズ株式会社 Dispositif de mesure de distance et procédé de mesure de distance
JP2022166693A (ja) * 2021-04-21 2022-11-02 シャープセミコンダクターイノベーション株式会社 光センサ、電子機器、距離算出方法、および、プログラムの記録媒体
US11493601B2 (en) 2017-12-22 2022-11-08 Innovusion, Inc. High density LIDAR scanning
US11762093B2 (en) 2017-03-01 2023-09-19 Ouster, Inc. Accurate photo detector measurements for LIDAR
US11808888B2 (en) 2018-02-23 2023-11-07 Innovusion, Inc. Multi-wavelength pulse steering in LiDAR systems
US11988773B2 (en) 2018-02-23 2024-05-21 Innovusion, Inc. 2-dimensional steering system for lidar systems
US12228649B2 (en) 2018-12-11 2025-02-18 Mitsubishi Electric Corporation Distance measurement correction device, distance measurement correction system, distance measurement correction method, and computer readable medium

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS6316283A (ja) * 1986-07-08 1988-01-23 Matsushita Seiko Co Ltd 人体検知装置
JPH10105687A (ja) * 1996-10-01 1998-04-24 Mitsubishi Electric Corp 監視用画像処理装置
JP2003202373A (ja) * 2002-01-07 2003-07-18 Omron Corp 移動物体検知装置および移動物体検知方法
JP2005300259A (ja) * 2004-04-08 2005-10-27 Ishikawajima Harima Heavy Ind Co Ltd 移動物体検出装置及び方法
JP2006322834A (ja) * 2005-05-19 2006-11-30 Nikon Corp 距離測定装置、及び距離測定方法
JP2010097412A (ja) * 2008-10-16 2010-04-30 Nohmi Bosai Ltd 煙検出装置
JP2012225825A (ja) * 2011-04-21 2012-11-15 Hino Motors Ltd レーダ装置、バス、および乗客移動検出方法、並びにプログラム

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2520232A (en) * 2013-08-06 2015-05-20 Univ Edinburgh Multiple Event Time to Digital Converter

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS6316283A (ja) * 1986-07-08 1988-01-23 Matsushita Seiko Co Ltd 人体検知装置
JPH10105687A (ja) * 1996-10-01 1998-04-24 Mitsubishi Electric Corp 監視用画像処理装置
JP2003202373A (ja) * 2002-01-07 2003-07-18 Omron Corp 移動物体検知装置および移動物体検知方法
JP2005300259A (ja) * 2004-04-08 2005-10-27 Ishikawajima Harima Heavy Ind Co Ltd 移動物体検出装置及び方法
JP2006322834A (ja) * 2005-05-19 2006-11-30 Nikon Corp 距離測定装置、及び距離測定方法
JP2010097412A (ja) * 2008-10-16 2010-04-30 Nohmi Bosai Ltd 煙検出装置
JP2012225825A (ja) * 2011-04-21 2012-11-15 Hino Motors Ltd レーダ装置、バス、および乗客移動検出方法、並びにプログラム

Cited By (39)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017195755A1 (fr) * 2016-05-13 2017-11-16 コニカミノルタ株式会社 Système de surveillance
WO2017195754A1 (fr) * 2016-05-13 2017-11-16 コニカミノルタ株式会社 Système de surveillance
WO2017195753A1 (fr) * 2016-05-13 2017-11-16 コニカミノルタ株式会社 Système de surveillance
JPWO2017195753A1 (ja) * 2016-05-13 2019-03-14 コニカミノルタ株式会社 監視システム
JPWO2017195754A1 (ja) * 2016-05-13 2019-03-22 コニカミノルタ株式会社 監視システム
JP2017227454A (ja) * 2016-06-20 2017-12-28 三菱電機株式会社 監視装置
JP7054989B2 (ja) 2016-06-20 2022-04-15 三菱電機株式会社 監視装置
JP2018067127A (ja) * 2016-10-19 2018-04-26 三菱電機株式会社 監視用画像処理装置および監視装置
JP2018105638A (ja) * 2016-12-22 2018-07-05 三菱電機株式会社 監視装置
US12248095B2 (en) 2016-12-31 2025-03-11 Seyond, Inc. 2D scanning high precision LiDAR using combination of rotating concave mirror and beam steering devices
US11782131B2 (en) 2016-12-31 2023-10-10 Innovusion, Inc. 2D scanning high precision LiDAR using combination of rotating concave mirror and beam steering devices
JP7273898B2 (ja) 2016-12-31 2023-05-15 イノビュージョン インコーポレイテッド 回転凹面鏡及びビームステアリング装置の組み合わせを用いた、２ｄ走査型高精度ライダー
US12276755B2 (en) 2016-12-31 2025-04-15 Seyond, Inc. 2D scanning high precision LiDAR using combination of rotating concave mirror and beam steering devices
JP2021004888A (ja) * 2016-12-31 2021-01-14 イノビュージョン アイルランド リミテッドＩｎｎｏｖｕｓｉｏｎ Ｉｒｅｌａｎｄ Ｌｉｍｉｔｅｄ 回転凹面鏡及びビームステアリング装置の組み合わせを用いた、２ｄ走査型高精度ライダー
US11977183B2 (en) 2016-12-31 2024-05-07 Seyond, Inc. 2D scanning high precision LiDAR using combination of rotating concave mirror and beam steering devices
JP2021177183A (ja) * 2016-12-31 2021-11-11 イノビュージョン アイルランド リミテッドInnovusion Ireland Limited 回転凹面鏡及びビームステアリング装置の組み合わせを用いた、２ｄ走査型高精度ライダー
US11782132B2 (en) 2016-12-31 2023-10-10 Innovusion, Inc. 2D scanning high precision LiDAR using combination of rotating concave mirror and beam steering devices
US12241999B2 (en) 2016-12-31 2025-03-04 Seyond, Inc. 2D scanning high precision LiDAR using combination of rotating concave mirror and beam steering devices
US11393185B2 (en) 2017-02-06 2022-07-19 Mitsubishi Electric Corporation Monitoring device
EP3579181A4 (fr) * 2017-02-06 2020-02-12 Mitsubishi Electric Corporation Dispositif de surveillance
US11762093B2 (en) 2017-03-01 2023-09-19 Ouster, Inc. Accurate photo detector measurements for LIDAR
JP7134988B2 (ja) 2017-03-01 2022-09-12 アウスター インコーポレイテッド ライダーのための正確な光検出器測定
JP2020512544A (ja) * 2017-03-01 2020-04-23 アウスター インコーポレイテッド ライダーのための正確な光検出器測定
JP7128568B2 (ja) 2017-09-05 2022-08-31 三菱電機株式会社 監視装置
JP2019046295A (ja) * 2017-09-05 2019-03-22 三菱電機株式会社 監視装置
US12189058B2 (en) 2017-12-22 2025-01-07 Seyond, Inc. High resolution LiDAR using high frequency pulse firing
US11493601B2 (en) 2017-12-22 2022-11-08 Innovusion, Inc. High density LIDAR scanning
US11988773B2 (en) 2018-02-23 2024-05-21 Innovusion, Inc. 2-dimensional steering system for lidar systems
US11808888B2 (en) 2018-02-23 2023-11-07 Innovusion, Inc. Multi-wavelength pulse steering in LiDAR systems
JP2019159723A (ja) * 2018-03-12 2019-09-19 株式会社デンソーウェーブ 静止物監視装置
WO2020090287A1 (fr) * 2018-10-29 2020-05-07 古野電気株式会社 Appareil et procédé de mesure de cible
US12228649B2 (en) 2018-12-11 2025-02-18 Mitsubishi Electric Corporation Distance measurement correction device, distance measurement correction system, distance measurement correction method, and computer readable medium
JP7592498B2 (ja) 2020-01-16 2024-12-02 パイオニア株式会社 反射データ処理装置、反射データ処理方法、およびプログラム
JP2021113807A (ja) * 2020-01-16 2021-08-05 パイオニア株式会社 反射データ処理装置、反射データ処理方法、およびプログラム
JPWO2022085310A1 (fr) * 2020-10-20 2022-04-28
WO2022085310A1 (fr) * 2020-10-20 2022-04-28 ソニーセミコンダクタソリューションズ株式会社 Dispositif de mesure de distance et procédé de mesure de distance
JP7710461B2 (ja) 2020-10-20 2025-07-18 ソニーセミコンダクタソリューションズ株式会社 距離測定装置及び距離測定方法
JP2022166693A (ja) * 2021-04-21 2022-11-02 シャープセミコンダクターイノベーション株式会社 光センサ、電子機器、距離算出方法、および、プログラムの記録媒体
JP7713797B2 (ja) 2021-04-21 2025-07-28 シャープセミコンダクターイノベーション株式会社 光センサ、電子機器、距離算出方法、および、プログラムの記録媒体

Also Published As

Publication number Publication date
JP6309099B2 (ja) 2018-04-11
JPWO2016002776A1 (ja) 2017-04-27

Similar Documents

Publication Publication Date Title
JP6309099B2 (ja) 監視装置
EP3309583B1 (fr) Appareil, procédé et programme de mesure de la distance
KR20190106765A (ko) 카메라 및 이미지 데이터를 검출하기 위한 방법
US20200380653A1 (en) Image processing device and image processing method
CN112534474A (zh) 纵深取得装置、纵深取得方法以及程序
US20170124418A1 (en) System and a method for the detection of multiple number-plates of moving cars in a series of 2-d images
JP7157118B2 (ja) コードリーダ及び光学コードの読み取り方法
CN110431562B (zh) 图像识别装置
JP2017146298A (ja) 形状測定システム、形状測定装置及び形状測定方法
KR20190088089A (ko) 용접 표면 결점 검출 장치 및 방법
JP4389602B2 (ja) 物体検出装置、物体検出方法、プログラム
JP2016009474A (ja) 物体識別システム、情報処理装置、情報処理方法及びプログラム
CN114868037B (zh) 信息处理装置、摄像装置、信息处理方法及存储介质
JPWO2018147059A1 (ja) 画像処理装置、および画像処理方法、並びにプログラム
CN112446225A (zh) 光学代码的模块尺寸的确定
WO2010055558A1 (fr) Dispositif d’extraction de zone de caractères, dispositif d’acquisition d’images doté d’une fonction d’extraction de zone de caractères et programme d’extraction de zone de caractères
KR20240023447A (ko) 3d 스캐너의 스캔 볼륨 모니터링
JP2017521011A (ja) シンボルの光学的検出方法
KR100920764B1 (ko) 고밀도의 광학 심볼을 2단계로 해독하기 위한 장치 및 방법
KR101705061B1 (ko) 차량 번호판의 글자 인식을 위한 번호판 검출방법
JP2014179762A (ja) 画像処理装置、オブジェクト検出方法、およびオブジェクト検出プログラム
CN115909254B (zh) 一种基于摄像头原始图像的dms系统及其图像处理方法
JP2007264742A (ja) 顔検出方法おならびにこれを用いた撮影装置
JP2010060371A (ja) 物体検出装置
JP4765113B2 (ja) 車両周辺監視装置、車両、車両周辺監視用プログラム、車両周辺監視方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 15814259

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2016531393

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 15814259

Country of ref document: EP

Kind code of ref document: A1