JP2017204838A - Information processing apparatus and information processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To count the number of people in a wider range.SOLUTION: An information processing apparatus comprises: detection means that detects specific objects in a first range from an image obtained by photographing the first range; first calculation means that calculates the number of the specific objects in the first range on the basis of a result of detection performed by the detection means; and second calculation means that calculates the number of the specific objects in a second range larger than the first range on the basis of the number calculated by the first calculation means.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an information processing apparatus and an information processing method.

  Conventionally, a method of counting the number of people in an image by analyzing an image captured by a surveillance camera is known. For example, Patent Document 1 discloses a technique for detecting a person within a shooting range by analyzing a moving image. Patent Document 2 discloses a technique for counting the number of people who have passed a predetermined area by tracking a detected person.

Japanese Patent Laying-Open No. 2015-70359 JP 2008-217205 A

  However, in the techniques disclosed in Patent Documents 1 and 2, the detection range of a person is limited to the shooting range.

  The present invention has been made in view of these problems, and an object thereof is to provide a processing technique that makes it possible to count the number of people in a wider range.

  One embodiment of the present invention relates to an information processing apparatus. The information processing apparatus includes: a detecting unit that detects a specific object in the first range from an image obtained by imaging the first range; and the number of specific objects in the first range based on a detection result by the detecting unit. And a second calculation means for calculating the number of specific objects in a second range larger than the first range based on the number calculated by the first calculation means. .

  According to the present invention, the number of people can be counted for a wider range.

1 is a schematic diagram of an information processing system including an information processing apparatus according to an embodiment. The block diagram which shows the function and structure of the network camera of FIG. The block diagram of the information processing apparatus of FIG. The block diagram which shows the function and structure of the analysis process part of Fig.3 (a). The data structure figure of the table hold | maintained at a recording part. The typical screen figure of the setting screen displayed on a display. 2 is a flowchart showing a series of processes in the information processing apparatus of FIG. The schematic diagram for demonstrating the count process using an object tracking. The schematic diagram for demonstrating the application example of the count process of the number of people. The schematic diagram for demonstrating another application example of the count process of the number of people. The schematic diagram for demonstrating another example of application of the count process of the number of people.

  Embodiments of the present invention will be described below with reference to the drawings. However, embodiments of the present invention are not limited to the following embodiments. The same or equivalent components, members, and processes shown in the drawings are denoted by the same reference numerals, and repeated descriptions are omitted as appropriate. In addition, in the drawings, some of the members that are not important for explanation are omitted.

  The information processing apparatus according to the embodiment performs human detection on an image suitable for human detection among images such as a moving image and a still image obtained from an imaging device such as a camera that performs preset patrol. Calculate the number of people. The information processing apparatus estimates the number of people in the target range from the size of the range corresponding to the image on which the person is detected, the calculated number of people, and the size of the target range for which the number of people is to be counted. As a result, the existing preset patrol function provided for the purpose of monitoring or the like can be used together for counting the number of people.

(Embodiment)
FIG. 1 is a schematic diagram of an information processing system 100 including an information processing apparatus 103 according to an embodiment. The information processing system 100 includes an information processing apparatus 103 and at least one network camera 102. The information processing apparatus 103 and the network camera 102 are connected via a network 101 such as the Internet.

  The network camera 102 may be a surveillance camera installed in a theater, a movie theater, a stadium or the like, and is configured to be able to control pan-tilt-zoom (hereinafter referred to as “PTZ”). The network camera 102 has a pan and tilt control pan head. The network camera 102 distributes moving images to the network 101.

  The information processing apparatus 103 performs control of the pan head of the network camera 102 and the image quality of the moving image from the network camera 102, and analyzes the moving image distributed from the network camera 102. A plurality of network cameras 102 and information processing apparatuses 103 may exist.

  Hereinafter, the process of counting the number of people by the information processing apparatus 103 according to the embodiment will be described. FIG. 2 is a block diagram showing functions and configuration of the network camera 102 of FIG. The network camera 102 includes an imaging unit 201, a camera control unit 202, a processing unit 203, a communication unit 204, and a storage unit 205.

The imaging unit 201 generates a moving image by imaging an imaging target region in real space. The imaging unit 201 includes an imaging device such as a CCD (Charge Coupled Device) and a CMOS (Complementary MOS) image sensor, a pan for changing the imaging direction, and a mechanism for changing imaging settings such as zoom, focus, and aperture. , A mechanism for performing masking processing and time superimposition processing on a moving image, and an image processing mechanism for changing luminance and color tone.
The camera control unit 202 controls the imaging unit 201 in response to the control command.

  The processing unit 203 receives a request command from the outside via the communication unit 204, and analyzes and executes the received request command. For example, if the request command is a command related to a request for control of the network camera 102, the processing unit 203 converts the command into a control command and sends it to the camera control unit 202. The camera control unit 202 executes the received control command. If the request command is a command related to an inquiry about the setting state of the network camera 102, the processing unit 203 acquires the corresponding state from the storage unit 205, converts it into a response format, and sends it back.

The communication unit 204 communicates with other devices. The communication unit 204 is connected to the network 101 and functions as an interface with the network 101.
The storage unit 205 stores model information, names, settings, and the like of the network camera 102.

  FIG. 3A is a block diagram illustrating the function and configuration of the information processing apparatus 103 in FIG. The information processing apparatus 103 includes a communication unit 301, a camera state management unit 302, a command management unit 303, a moving image management unit 304, an analysis processing unit 305, a storage unit 306, a recording unit 307, and a reception unit 308. An input unit 309, a display control unit 310, and a display 311.

The communication unit 301 communicates with other devices. The communication unit 301 is connected to the network 101 and functions as an interface with the network 101.
The camera status management unit 302 acquires the status of the camera 102 from the network camera 102 to be analyzed, or receives a status change notification from the camera. The camera state management unit 302 grasps and manages the state of the camera platform and the imaging mechanism of the network camera 102 based on the acquired state or the received notification. The camera state management unit 302 associates the state of the network camera 102 with the time and registers them in the camera state table 502 (described later in FIG. 5B).

  The command management unit 303 generates and transmits a request command for changing the camera platform and imaging mechanism of the network camera 102 to a desired state and a request command for acquiring a moving image from the network camera 102.

  The moving image management unit 304 functions as an acquisition unit that acquires a moving image captured by the network camera 102 from the network camera 102 via the network 101. The moving image management unit 304 acquires and manages moving images distributed from the network camera 102. In the present embodiment, the command management unit 303 requests the network camera 102 for a moving image with a resolution (1280 × 720, 640 × 360, 320 × 180, etc.), frame rate, and format prior to the counting process of the number of people. The moving image management unit 304 receives a moving image transmitted from the network camera 102 in response to the request. As settings such as the designated resolution, frame rate, and format, settings that should be used in another process such as a monitoring process that is performed in parallel with the count process of the number of people may be used. Alternatively, the information processing apparatus 103 may apply an optimum setting for the number counting process.

The analysis processing unit 305 detects a person in the image and counts the detected person with respect to the moving image from the network camera 102.
The storage unit (Storage unit) 306 is a RAM (Random Access Memory) that temporarily stores programs and data, and temporarily stores the results of the analysis processing executed by the analysis processing unit 305. The storage unit 306 also obtains the state of the network camera 102 at the time when the image subjected to the analysis process was captured from the camera state management unit 302 and temporarily stores it.

A recording unit 307 is a hard disk, an optical disk, a memory card, or the like, and records settings in the network camera 102.
The input unit 309 is a device operated by a user for input, such as a pointing device such as a mouse or a keyboard.
The accepting unit 308 accepts user input such as range designation from the user via the input unit 309.
The display 311 is a CRT (Cathode Ray Tube), an LCD (Liquid Crystal Display), or the like. The display control unit 310 controls the display 311.
The display control unit 310 generates data corresponding to the screen to be displayed on the display 311 and provides the data to the display 311.

  FIG. 3B is a hardware configuration diagram of the information processing apparatus 103 in FIG. The CPU 320 mainly controls the operation of each component. The main memory 321 stores a control program executed by the CPU 320 and provides a work area when the CPU 320 executes the program. The magnetic disk 322 is an example of an external storage device that stores an operating system (OS), device drivers for peripheral devices, and programs for realizing various application software including programs for performing processing described later. is there. When the CPU 320 executes the programs stored in the main memory 321 and the magnetic disk 322, the functions (software) of the information processing apparatus 103 shown in FIG. The program stored in the magnetic disk 322 is expanded in the main memory 321 as necessary, and is executed by the CPU 320. The display memory 323 temporarily stores display data. The mouse 324 and the keyboard 325 are as described above. The above components are connected to each other via a common bus 326 so that they can communicate with each other.

  In the example shown in FIG. 3B, only one CPU 320 is illustrated as hardware, but a plurality of CPUs may be included. Or you may have GPU. In any case, a plurality of arithmetic processing units (processors) such as a CPU and a GPU may be provided as hardware resources. Further, a plurality of magnetic disks 322 for storing programs may be provided. Alternatively, in another embodiment, at least some or all of the functions shown in FIG. 3A may be implemented as one or more dedicated hardware circuits.

  FIG. 4 is a block diagram showing the function and configuration of the analysis processing unit 305 in FIG. The analysis processing unit 305 includes a preset tour setting unit 401, a target range setting unit 402, a state acquisition unit 403, a moving image acquisition unit 404, a determination unit 405, a detection unit 406, an imaging number calculation unit 407, And the total number of people calculation unit 408. 5A, 5B, and 5C are data structure diagrams showing examples of the preset table 501, the camera state table 502, and the count result table 503, respectively. These tables are held in the recording unit 307.

  The preset tour setting unit 401 performs control settings of the network camera 102, for example, preset tour settings. A set of parameters (pan, tilt) for specifying the state of the camera platform and parameters (zoom, focus, aperture) for specifying the imaging setting are referred to as a preset. In the preset tour, a plurality of different presets are set. Furthermore, in the preset tour, the order of the presets, the operating speed of the pan head when changing the presets, and the standby time after the setting is changed to each preset are set. These are collectively referred to as preset patrol settings. The network camera 102 is set so that a plurality of predetermined ranges are sequentially imaged by preset tour settings. Each of the plurality of predetermined ranges corresponds to each of a plurality of different presets included in the preset tour setting. Hereinafter, each of the plurality of predetermined ranges is referred to as a preset imaging range.

  The preset tour setting unit 401 receives designation of preset tour settings from the user via the reception unit 308 and the input unit 309. The preset tour setting unit 401 stores the designated preset tour setting in the preset table 501 (FIG. 5A). The preset table 501 holds a preset ID for specifying a preset, a preset (pan, tilt, zoom, focus, aperture), an operation speed, and a standby time in association with each other. The preset ID specifies the preset and represents the order of the preset in the preset tour. In the example of FIG. 5A, the preset tour starts from the preset included in the entry of the preset ID “1”, and transitions in order of the preset IDs “1”, “2”, “3”,. The preset tour returns to the preset ID “1” when the standby time “rs” elapses with the preset of the preset ID “13”. The operation of the network camera 102 will be described. The network camera 102 images the preset imaging range corresponding to the preset ID “1”, and then images the preset imaging range corresponding to the preset ID “2”. When the network camera 102 captures images in order of the preset IDs “3”, “4”,... And captures the last preset imaging range corresponding to the preset ID “13”, the first preset imaging corresponding to the preset ID “1” is performed. Return to range imaging.

  The target range setting unit 402 sets a target range for counting the number of people and stores it in the recording unit 307. The target range setting unit 402 causes the display 311 to display a setting screen for setting the target range via the display control unit 310. The target range setting unit 402 receives the target range specified on the setting screen by the user using the input unit 309 via the receiving unit 308. The target range setting unit 402 stores the specified target range in the recording unit 307.

  FIG. 6 is a representative screen diagram of the setting screen 601 displayed on the display 311. The setting screen 601 has an imageable range 602, a target range 603, and an imaging range 604. The imageable range 602 is an imageable range calculated from the operable range of the camera platform of the target network camera 102 and the imaging angle of view. The imaging range 604 is an imaging range calculated from the current imaging state of the target network camera 102. The user draws the target range 603 on the setting screen 601 using a pointing device such as a mouse. A target range 603 illustrated in FIG. 6 is an example of a target range set by the user. The target range 603 is normally set larger than the imaging range 604. As described above, the setting screen 601 enables the user to specify the target range 603 for the imageable range 602 of the network camera 102.

  Note that a panoramic image obtained by combining images captured by the network camera 102 may be displayed on the background of the imageable range 602. Further, the target range 603 may be set larger than the imageable range 602.

  Returning to FIG. 4, when a change to a new preset is requested in the preset tour, the status acquisition unit 403 displays the status of the network camera 102 set according to the preset so far in the camera status table 502 (FIG. 5 ( obtained from b)). The camera state table 502 holds the time and the state (pan, tilt, zoom, focus, aperture, resolution, frame rate, format) of the network camera 102 at that time in association with each other. The state acquisition unit 403 specifies a state to be obtained using the time as a key in the camera state table 502, and acquires the specified state.

  The moving image acquisition unit 404 acquires a moving image corresponding to the state acquired by the state acquisition unit 403 from the moving image management unit 304. That is, when a change to a new preset is requested, the moving image acquisition unit 404 acquires a moving image obtained by imaging a preset imaging range corresponding to the previous preset.

  The determination unit 405 determines whether or not the moving image acquired by the moving image acquisition unit 404 satisfies a criterion related to human detection. If it is determined that the number is satisfied, the counting process for the number of persons is performed. Otherwise, the counting process for the number of persons is not performed or is skipped. For example, the determination unit 405 calculates an index indicating whether or not the subject is in focus, for example, the degree of focusing of the moving image, from the acquired moving image or the state of the network camera 102. The determination unit 405 determines that the criterion is satisfied when the calculated degree exceeds the degree necessary for human detection, and determines that it is not satisfied otherwise. In another example, the determination unit 405 calculates the distance to the subject from the acquired state of the network camera 102. The determination unit 405 calculates the number of pixels occupied by the preset imaging range on the imaging element of the imaging unit 201 from the calculated distance and zoom state. The determination unit 405 determines that the criterion is satisfied when the calculated number of pixels exceeds the number of pixels necessary for human detection, and determines that the criterion is not satisfied otherwise. This corresponds to the fact that human detection is not performed when the image quality required for human detection cannot be obtained due to the large digital zoom.

  If the determination unit 405 determines that the condition is satisfied, the detection unit 406 detects a person in the preset imaging range from the moving image acquired by the moving image acquisition unit 404. The human detection process in the detection unit 406 may be realized using a known image recognition technique.

  The number-of-imaging number calculation unit 407 calculates the number of people in the preset imaging range based on the detection result by the detection unit 406. The imaging number calculation unit 407 registers the calculated number of people in the count result table 503 (FIG. 5C) in association with the state acquired by the state acquisition unit 403. As a result, in the count result table 503, the number of people counted corresponding to each preset is registered. The count result table 503 holds the state (pan, tilt, zoom, focus, aperture, resolution, frame rate, format) of the network camera 102 corresponding to the preset and the counted number of people in association with each other. When the state of the network camera 102 to be registered is already registered in the count result table 503, the number-of-imaging number calculation unit 407 may update, that is, overwrite the number of people corresponding to the state. Note that such a situation occurs after the second round of the preset tour, for example, and the number of people registered in the first round is overwritten with the number of people counted in the same preset in the second round.

  The total number calculation unit 408 calculates the number of people in the target range based on the number of people calculated by the imaging number calculation unit 407, the size of the preset imaging range, and the size of the target range. Specifically, the total number of people calculation unit 408 refers to the count result table 503 and identifies a set of an available state and the number of people counted. For example, when a change to the preset ID “5” is requested in the first round of the preset tour, a combination of a state and the number of people corresponding to each of the preset IDs “1”, “2”, “3”, and “4” Will be available. From the second round onward, depending on the determination result by the determination unit 405, there may be cases where pairs corresponding to all the preset IDs can be used. The total number of people calculation unit 408 calculates the size of the preset imaging range corresponding to each specified set. The total number calculation unit 408 adds up the calculated sizes of the preset imaging range. The total number of people calculation unit 408 adds up the specified number of people. The total number of people calculation unit 408 acquires the size of the target range from the recording unit 307. When there is no overlap between the preset imaging ranges, the total number calculation unit 408 multiplies the total number of people by a value obtained by dividing the size of the acquired target range by the total size of the preset imaging range. Calculate the number of people in the target range.

  When there is an overlap, the total number calculation unit 408 further obtains an effective size by adding the sum of the sizes of the overlapping portions to the total size of the preset imaging range. The total size of the overlapping parts represents the degree of overlapping. The total number of persons calculating unit 408 calculates the number of persons in the target range by multiplying the total number of persons by a value obtained by dividing the size of the acquired target range by the effective size. If there is an overlap, the number of people detected at the overlap is counted multiple times, so the total number of people is greater than the total number of actual people. However, since the size of the overlapping portion is added to the size of the preset imaging range, the ratio value is not so different from the actual value. Thus, an estimated value of the number of people in the target range can be obtained without actually counting how many people are in the overlapping portion. This is based on the standpoint that since the number of people calculated by the total number of people calculation unit 408 is an estimated value, it is not necessary to strictly perform only the overlapping process and increase the processing load. Of course, the number of people in the target range may be estimated more accurately by counting how many people are in the overlapping portion.

  The total number calculation unit 408 may calculate the number of people in the target range using the number of people overwritten by the imaging number calculation unit 407. In this case, the number of people in the target range is calculated based on the number of people in the preset imaging range after the second round instead of the number of people in the preset imaging range obtained in the first round of the preset tour.

The operation of the information processing apparatus 103 configured as above will be described.
FIG. 7A is a flowchart showing a series of processes in the information processing apparatus 103 in FIG. In step S <b> 701, the analysis processing unit 305 acquires the target range setting from the recording unit 307. In step S <b> 702, the command management unit 303 acquires the preset tour setting from the preset table 501 held in the recording unit 307. In step S <b> 703, the command management unit 303 determines whether the reception unit 308 has received a preset tour end instruction from the user. If accepted (YES in S703), the process ends. If not accepted (NO in S703), in S704, the command management unit 303 determines whether or not the current preset waiting period has expired. The waiting period is a period having a length designated by the waiting time, starting from when the preset is set. If it has not expired (NO in S704), the command management unit 303 repeats S704. If it has expired (YES in S704), in step S705, the command management unit 303 refers to the preset tour setting acquired in step S702, and acquires the current preset by specifying the next preset. In step S <b> 706, the command management unit 303 generates a request command for changing the camera platform or the imaging mechanism of the network camera 102 to a state specified by the acquired preset, and transmits the request command to the network camera 102. In step S <b> 707, the analysis processing unit 305 executes a count process for the number of people, triggered by the transmission of the request command in step S <b> 706. Thereafter, the process returns to S703. If the current preset is the last preset of the preset tour setting in S705, the first preset is acquired as the next preset.

  FIG. 7B is a flowchart showing a series of processes performed in the process of counting the number of people in FIG. In step S <b> 708, the state acquisition unit 403 acquires the state of the network camera 102. In step S709, the moving image acquisition unit 404 acquires a moving image obtained by imaging the preset imaging range to be counted. In S710, the determination unit 405 determines whether or not a criterion necessary for detecting a person is satisfied. If not satisfied (NO in S710), the process proceeds to S714. When satisfied (YES in S710), in S711, the detection unit 406 detects a person from the acquired moving image. In step S <b> 712, the number-of-images calculation unit 407 calculates the number of detected people. In step S713, the imaging number calculation unit 407 stores the calculated number in the count result table 503 in association with the state acquired in step S708. In step S <b> 714, the total number of people calculation unit 408 acquires the number of people calculated in the past from the count result table 503. In S715, the total number of people calculation unit 408 calculates the estimated number of people in the target range based on the acquired past number of people.

  According to the information processing apparatus 103 according to the present embodiment, it is possible to obtain an estimated value of the number of persons in the entire target range from the result of the number of persons for an image obtained by capturing a part of the target range of the person count.

  The configuration and operation of the information processing apparatus 103 according to the embodiment has been described above. This embodiment is an exemplification, and it is understood by those skilled in the art that various modifications can be made to each component and combination of processes, and such modifications are within the scope of the present invention.

(Modification)
In the present embodiment, the case where the number counting process is performed in accordance with the preset patrol process has been described. However, the present invention is not limited to this, and the number counting process may be executed alone. Alternatively, the process of counting the number of people may be executed together with a process other than the preset patrol process. More generally, when there is a target range for counting the number of a specific object such as a person and an image obtained by imaging an imaging range smaller than the target range, the technology according to the present embodiment The number in the target range can be estimated by applying the philosophy.

  In this embodiment, the case where the user sets the target range and registers the setting in the recording unit 307 has been described. However, the present invention is not limited to this, and the target range may be a predetermined fixed range, for example. .

  In the present embodiment, a case has been described where the number of people is counted every time a preset change request is transmitted in a preset tour, but the present invention is not limited to this. For example, the number of people may be counted each time a new image is received from the network camera 102. Alternatively, the number of people may be counted every other preset that changes in order, or the number of people may be counted each time the preset tour is completed. In the present embodiment, the real-time property can be improved by updating the estimated value of the number of people in the target range more frequently than in the above modification.

  In addition, a moving image (hereinafter referred to as “moving moving image”) captured by the network camera 102 while the network camera 102 changes from a state for capturing a preset imaging range to a state for capturing the next preset imaging range. May be used for counting people. The detection unit according to this modification detects a person by performing an object tracking process on the moving moving image.

  FIG. 8 is a schematic diagram for explaining a counting process using object tracking. In FIG. 8, it is assumed that the state of the network camera 102 changes from a state for capturing the first preset imaging range 801 to a state for capturing the next second preset imaging range 802. The imaging range of the moving moving image captured during the change (hereinafter referred to as “moving imaging range”) is a range indicated by hatching in FIG. The moving image includes a number of frames including a first frame 803, a second frame 804, and a third frame 805. In this modification, the detection unit detects a person using object tracking from each frame while omitting duplication. For example, the detection unit detects the first person 806 and the second person 807 from the first frame 803. Next, the detection unit detects the second person 807 and the third person 808 from the second frame 804, but also recognizes that the second person 807 was also detected in the first frame 803 by object tracking processing. . The detection unit detects only the third person 808 from the result of the object tracking process. Similarly, the detection unit detects two people from the third frame 805 except for the third person 808 detected in the second frame 804. Note that the object tracking process itself may be realized using a known image recognition technique. As described above, the detection unit detects a person in the moving imaging range while removing the overlap, and the imaging number calculation unit calculates the number of detected people. The number-of-imaging-number calculating unit registers the imaging conditions (pre- and post-presets, etc.) of moving images during movement in association with the calculated number of people in the count result table. In the subsequent processing, the number of persons in the target range can be estimated as described in the embodiment by handling the moving imaging range in the same manner as the preset imaging range.

  The determination unit according to the present modification has a speed at which the state of the network camera 102 changes from the state for capturing the first preset imaging range 801 to the state for capturing the next second preset imaging range 802. It is determined whether or not criteria for detection are satisfied. The determination unit obtains an imaging angle of view, a shutter speed, and a pan head operation speed from the state of the network camera 102. The determination unit calculates a moving speed with respect to the angle of view (not the operating speed of the camera platform) from the acquired parameters. The determination unit determines that the criterion is satisfied when the calculated moving speed is lower than a moving speed at which an image with little or no blur necessary for human detection is obtained, and determines that the criterion is not satisfied otherwise. . When it is determined that the criterion is satisfied, the detection unit detects a person in the moving image.

  Alternatively, the determination unit calculates the overlap of the imaging ranges of the first frame 803 and the second frame 804 when detecting a person from the second frame 804, and determines whether the overlap is equal to or greater than a threshold value. . If the overlap of the imaging ranges is smaller than the threshold value, the person is detected from the second frame 804 without performing object tracking. This corresponds to the fact that when the overlap is small, the influence of the overlap on the estimated value is small. If the overlap of the imaging ranges is equal to or greater than the threshold value, the person is detected while performing the object tracking.

  In this modification, the detection unit may change the detection sensitivity according to the moving speed with respect to the angle of view. For example, the detection unit detects even one frame when the moving speed is high, that is, exceeds the threshold, and when a certain person hits several frames consecutively when the moving speed is low, that is, below the threshold The person may be detected.

(Application examples)
Hereinafter, application examples of the count processing of the number of persons by the information processing apparatus according to the above-described embodiments and modifications will be described. FIG. 9 is a schematic diagram for explaining an application example of the number counting process. In this application example, the network camera 102 is a surveillance camera attached to the ceiling of the theater stage, and images the audience seats 901 in order according to preset patrol settings. In the application example of FIG. 9, there are a total of 18 preset imaging ranges PSR1 to PSR18, each of which is shown by a rectangle in FIG. The target range 902 is indicated by a broken-line rectangle. When the information processing apparatus is requested to move from the preset imaging range PSR2 to the preset imaging range PSR3 in the first round of the preset tour, the information processing apparatus calculates the number of people in the preset imaging range PSR2 as “4”. The information processing apparatus 103 refers to the count result table and acquires the number of people “5” calculated for the preset imaging range PSR1. When the area of the preset imaging range PSR1 is A1, the area of the preset imaging range PSR2 is A2, and the area of the target range 902 is A3, the information processing apparatus calculates the target range 902 by calculating (4 + 5) · A3 / (A1 + A2). Get an estimate of the number of people at.

  In the above calculation example, the number of people in the target range 902 is estimated on the assumption that the distribution density of people in the target range 902 is uniform. However, the calculation method is not limited to this, and for example, the perspective in the target range 902 may be considered. In the example shown in FIG. 9, the preset imaging range PSR1 is a range closer to the network camera 102, and a person appears relatively large in a moving image obtained by imaging the range. On the other hand, the preset imaging range PSR11 is a range farther from the network camera 102, and a person appears relatively small in a moving image obtained by imaging the range. When estimating the number of persons in the target range 902, the information processing apparatus determines the target range 902 as a proximal stage composed of PSR1 to PSR4, a middle stage composed of PSR5 to PSR10, and a distal stage composed of PSR11 to PSR18. It may be divided into three stages. The information processing apparatus may estimate the number of people for each of the three stages, and use the sum of the obtained three estimated values as the estimated number of people in the target range 902. Note that the division method of the target range 902 is not limited to the above three divisions, and may be appropriately divided according to the assumed distribution density of the count target.

  FIG. 10 is a schematic diagram for explaining another application example of the number counting process. In the application example of FIG. 10, there are a total of six preset imaging ranges PSR1, PSR4, PSR5, PSR10, PSR11, and PSR18, which are circulated in this order. The information processing apparatus calculates the number of people in each preset imaging range and stores it in the count result table, and also calculates the number of people in the moving imaging range between the preset imaging ranges. However, the moving imaging range when moving from the preset imaging range PSR5 to the preset imaging range PSR10 (indicated by hatching in FIG. 10) is not calculated because the moving speed with respect to the angle of view is too fast. The information processing apparatus moves the sum of the areas of the six preset imaging ranges, the area of the moving imaging range when moving from the preset imaging range PSR1 to the preset imaging range PSR4, and moves from the preset imaging range PSR11 to the preset imaging range PSR18. And the area of the moving imaging range when moving. The information processing apparatus obtains an estimated value of the number of people in the target range 902 by multiplying the total number of detected people by a value obtained by dividing the area of the target range 902 by the added area.

  FIG. 11 is a schematic diagram for explaining still another application example of the number counting process. In the application example of FIG. 11, there are two moving imaging ranges 903 and 904 that overlap each other. The information processing apparatus calculates the number of persons in each of the first moving imaging range 903 and the second moving imaging range 904 using the method according to the modification described in FIG. 8 and stores the number in the count result table. As described in the embodiment, the information processing apparatus calculates the number of persons in the target range in consideration of the area of the overlapping portion 905 (indicated by hatching in FIG. 11) of the two moving imaging ranges 903 and 904. To do. In this way, the embodiment and the modification can be combined.

(Other examples)
The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

  100 information processing system, 101 network, 102 network camera, 103 information processing apparatus.

Claims (14)

Detecting means for detecting a specific object in the first range from an image obtained by imaging the first range;
First calculation means for calculating the number of specific objects in the first range based on a result of detection by the detection means;
And second calculation means for calculating the number of the specific objects in a second range larger than the first range based on the number calculated by the first calculation means. Processing equipment.   The second calculation means calculates the number of the specific objects in the second range based on the size of the first range and the size of the second range. The information processing apparatus according to 1.   The second calculation means multiplies the number calculated by the first calculation means by a value obtained by dividing the size of the second range by the size of the first range. The information processing apparatus according to claim 2, wherein the number of the specific objects in a range is calculated. Further comprising an acquisition means for acquiring an image obtained by imaging the first range from the imaging device;
4. The information processing apparatus according to claim 1, wherein the imaging apparatus is set so that a plurality of predetermined ranges including the first range are imaged in order. 5. The imaging device is set so as to return to the imaging of the first range when imaging the last range by imaging the plurality of predetermined ranges in order,
The first calculation means calculates the number of the specific objects in the first range after the second round,
The second calculation means may calculate the second calculation based on the number of the specific objects in the first range after the second round instead of the number of the specific objects in the first range in the first round. The information processing apparatus according to claim 4, wherein the number of the specific objects in a range is calculated. The detection means performs object tracking on a moving image captured by the imaging device while the state of the imaging device changes from a state for imaging the first range to a state for imaging the next predetermined range. The specific object is detected by processing,
The first calculation means calculates the number of the specific objects in the moving image,
6. The information according to claim 4, wherein the second calculation unit calculates the number of the specific objects in the second range based on the number of the specific objects in the moving image. Processing equipment. Determining whether or not the speed at which the state of the imaging device changes from the state for capturing the first range to the state for capturing the next predetermined range satisfies the criteria for detecting the specific object And a determination means for
The information processing apparatus according to claim 6, wherein the detection unit detects the specific object in the moving image when the determination unit determines that the condition is satisfied.   The information processing apparatus according to any one of claims 4 to 7, further comprising a reception unit configured to receive a designation of the second range with respect to an imageable range of the imaging apparatus from a user. A determination unit that determines whether an image obtained by imaging the first range satisfies a criterion related to detection of the specific object;
7. The information processing according to claim 1, wherein the detection unit detects the specific object in the first range when it is determined that the determination unit satisfies the condition. 7. apparatus.   The determination means determines that the criterion is satisfied when a degree of focusing of an image obtained by imaging the first range exceeds a degree necessary for detection of the specific object. The information processing apparatus described in 1.   The determination unit determines that the criterion is satisfied when the number of pixels occupied by the first range on the image sensor exceeds the number of pixels necessary for detection of the specific object. The information processing apparatus described in 1. The detection means detects the specific object in the third range from an image obtained by capturing a third range smaller than the second range,
The first calculating means calculates the number of the specific objects in the third range;
The second calculation means is configured to calculate the number of the specific objects in the first range, the number of the specific objects in the third range, and the overlap between the first range and the third range. The information processing apparatus according to claim 1, wherein the number of the specific objects in the second range is calculated based on the degree. Detecting a specific object in the first range from an image obtained by imaging the first range;
Calculating the number of specific objects in the first range based on the detection result;
Calculating the number of the specific objects in a second range larger than the first range based on the calculated number.   The program for functioning a computer as each means of the apparatus of any one of Claims 1 thru | or 12.

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