EP1486932A2 - Système de traitement d'images pour un véhicule - Google Patents

Système de traitement d'images pour un véhicule Download PDF

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Publication number
EP1486932A2
EP1486932A2 EP04013002A EP04013002A EP1486932A2 EP 1486932 A2 EP1486932 A2 EP 1486932A2 EP 04013002 A EP04013002 A EP 04013002A EP 04013002 A EP04013002 A EP 04013002A EP 1486932 A2 EP1486932 A2 EP 1486932A2
Authority
EP
European Patent Office
Prior art keywords
image processing
processing system
detected
collision
road users
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.)
Withdrawn
Application number
EP04013002A
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German (de)
English (en)
Other versions
EP1486932A3 (fr
Inventor
Stefan Dipl.-Inf. Hahn
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.)
Mercedes Benz Group AG
Original Assignee
DaimlerChrysler AG
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 DaimlerChrysler AG filed Critical DaimlerChrysler AG
Publication of EP1486932A2 publication Critical patent/EP1486932A2/fr
Publication of EP1486932A3 publication Critical patent/EP1486932A3/fr
Withdrawn legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes

Definitions

  • the invention relates to a method for operating a Image processing system for a vehicle as well Image processing system for a vehicle, in particular for Collision avoidance with other road users.
  • the capture The environment information is here by means of imaging Sensors. Where the captured image data then using be evaluated an image processing system. The Evaluation is usually done by checking Whether a permissible minimum distance becomes an obstacle or falls below a road user.
  • US 6496117 B2 describes a system for monitoring attention a driver.
  • the system comprises a camera, which scans the face of a driver.
  • the system furthermore comprises one unit each for determining the viewing direction as well as the facial position of the driver. It will determines whether the viewing direction as well as the facial position of the Driver oriented in the direction of the vehicle ahead are.
  • the system is with a warning device equipped, which warns the driver, if that Viewing or facial position not in the vehicle lying ahead direction are oriented.
  • An additional is a camera detects objects in the environment of the Vehicle. Where detected objects are evaluated, in particular what kind of object it is and in which distance this is to the vehicle. in this connection will depend on the line of sight and facial position of the driver and at the same time falling below a Minimum distance to objects triggered a warning signal.
  • JP 2002260192 A a method for preventing Collisions with other road users when used in Vehicles described.
  • information for avoidance be provided by collisions which the Include the behavior of other road users.
  • the risk of a collision is assessed by the behavior of other road users in relation to their own Vehicle is estimated.
  • This estimate is then determined whether the vehicle in a collision hazard if necessary can be slowed down in time.
  • the procedure is described by a pedestrian, which is in the Near a crossroads with a total of four crosswalks staying. This is based on geometric information of the Scene, the position of the pedestrian and possibly its direction of movement estimated which of the 4 crosswalks the Pedestrians will cross.
  • the invention is therefore based on the object, a method for operating an image processing system for a vehicle according to the preamble of claim 1 and a Image processing system for a vehicle according to the preamble of claim 11, whereby a reliable Person registration especially with regard to one possible assessment of a collision risk should.
  • a method for operating an image processing system for a vehicle comprises at least one image sensor for detecting environmental information.
  • the detected environment information is evaluated by means of a computer unit to detect the presence of road users.
  • the viewing direction of one or more detected road users is detected.
  • the detection of Looking towards one or more road users Estimation of a collision risk used. Where the Viewing direction of a road user indicates whether this is attentive and e.g. an approaching vehicle this road user is perceived. That's it Collision risk higher if the road user in the The image sensor opposite direction looks as if this, however, looks directly into the image sensor. That too is Collision risk higher if another road user just look roughly in the direction of the driver as if this direct eye contact with the driver stops.
  • a probability measure for estimation of collision risk is dependent the detected and evaluated viewing direction recognized Road users a probability measure for estimation of collision risk.
  • the Possibility that the probability measure directly based the relative angle between the line of sight of the Road user and the image sensor or the Direction of movement of the vehicle or of the Road user is determined.
  • the Probability for collision risk for example increases proportionally with this angle.
  • image sections of road users in different poses are deposited.
  • the image excerpts are deposited in such a way that they are part of a Training process for a classification method as Sample samples can be used. Being in the frame a classification every class a probability measure for the attention of road users and thus for the risk of collision.
  • the duration of the eye contact for estimating the Collision risks are used. It can be determined if an approaching Vehicle actually noticed by a road user or if a eye contact possibly only coincidentally has come.
  • Model information can be compared and from it Probability measure for the estimation of the collision risk be formed.
  • model data in both static as well as in dynamic databases.
  • This can be model data which both the Scene as well as other road users as well as their Describe vehicles and their movement.
  • geometric and dynamic model data used to describe the behavior of pedestrians. For example, when crossing a street with Pedestrian traffic light and without pedestrian lights or with one Crosswalk.
  • a probability measure for Estimation of the collision risk is formed. For example, so-called if-then-else Clauses or machine models are used.
  • a Another advantageous way is due to Movement information of the vehicle and / or the or recognized road users to a probability measure Assessment of the collision risk formed. For example if the motion information is the Speed, direction as well as trajectory with the one Vehicle and / or a recognized road user moves.
  • the Movement relative to your own vehicle determined to then a measure of probability for estimating the To form collision risk.
  • the distance to considered road users for example, based on the Image sensor is detected. This is e.g. in connection with 3D image sensors directly possible or when using 2D image sensors realized by means of a stereo arrangement.
  • the Partial probabilities which the direction of view and / or Model information and / or fixed rules and / or movement information of the vehicle and / or the or the recognized road users, too a total probability measure for the estimation of the Collision risk combined.
  • the Partial probabilities which the direction of view and / or Model information and / or fixed rules and / or movement information of the vehicle and / or the or the recognized road users, too a total probability measure for the estimation of the Collision risk combined.
  • the Partial probabilities which the direction of view and / or Model information and / or fixed rules and / or movement information of the vehicle and / or the or the recognized road users, too a total probability measure for the estimation of the Collision risk combined.
  • a preferred embodiment of the invention sees it before that, depending on the probability measure or of the total probability measure by means of a Control unit at least one action to reduce the Collision risk is initiated.
  • the at least one collision risk mitigating action is initiated as soon as one of the probability measures has exceeded a certain threshold.
  • Examples such actions are for example: Acoustic warning signals, the both the driver (buzzer) and other road users (Horn) can warn, optical signals, deceleration or Accelerating the vehicle, steering movements or others by vehicle systems feasible actions. Which These actions can also be carried out by the Depend on the amount of probability. For example, at a low probability initially only the horn activated. If the probability can increase further e.g. In addition, the brake of the vehicle can be activated. It is conceivable, the braking force in dependence of Chance to change.
  • the detected Environment information about 2D and / or 3D image information.
  • passive passive imaging sensors are suitable such.
  • active Image sensors such as distance image cameras conceivable.
  • optical sensors possible, wherein the sensitivity of the image sensors both in visible as well as in the non-visible wavelength range can lie.
  • the invention is not limited to use in Limited vehicles. Rather, it is also a use the image processing system according to the invention and the Method for its operation in a different field of application especially in connection with working machines advantageous effect.
  • Working area for safety reasons to persons is delimited. These include u.a. Turn u. milling machines, Saws, grinding machines, etc., using the Image processing system according to the invention Workspaces are monitored, for example, the Turn off the work machine in a dangerous situation and thus the traffic safety and thus the operational safety to increase.
  • it may be at the work machine act a robot, in the context of robots the Evaluation of the direction of view of persons, for example Improving the interaction between human and robot serves. It can be a stationary or mobile Robot act, which is autonomously operable.
  • Fig. 1 shows an example of the schematic structure of Image processing system (1) according to the invention.
  • the image processing system (1) road users in the Environment of a vehicle detected and if they move possibly also be tracked.
  • the road users to be recognized can be known to the image processing system (1) these are categorized by class and, for example, in the form of stored knowledge as learning examples in the Memory (6) can be stored.
  • class it can For example, pedestrians, cyclists, guide posts, Lane markers, cars, trucks, two-wheelers, skateboard riders etc. act.
  • the image processing system (1) comprises a Object recognition unit (2), which one or more Image sensors (3), a computing unit (4) and a Algorithm (5) for the evaluation of image information includes.
  • the image sensors (3) are e.g. around passive Sensors such as standard video cameras or to active sensors, e.g. Range cameras.
  • passive Sensors such as standard video cameras or to active sensors, e.g. Range cameras.
  • active sensors e.g. Range cameras.
  • pedestrians on the basis of their outer Form detected and their 3D position based on calibrated Camera parameters are estimated on the assumption that these together with the vehicle on a horizontal Level.
  • the classes the road user to be recognized Image processing system are not known. In this case These are usually due to a machine Description formulated on the basis of their spatial extent.
  • the image processing system (1) comprises a Collision Risk Estimation Unit (7) e.g. based on the viewing direction and / or the movement of Road users.
  • a Collision Risk Estimation Unit (7) e.g. based on the viewing direction and / or the movement of Road users.
  • the Kollisionsrisikos is fixed by means of fixed rules such. if-then-else clauses an implicit mapping between the Output of the object recognition system (2) and the control unit (7).
  • This illustration can be, for example, by means of the computer unit (4) or another processor, which in connection with the image processing system (1) stands to be performed.
  • Such an implicit picture can e.g. through the application of algorithms (5) for machine learning are generated. For example, by the train neural networks by means of the specification of Sample samples for a training process.
  • the as deposited knowledge part of the image processing system is the eye or head direction of a road user included in the picture, as shown in the image sections 2b and 3b is shown.
  • the alignment of the head is already a good one Approximation for the viewing direction of persons.
  • risk assessment is not on the use of neural networks limited to the expert In the field of pattern recognition are further suitable for this purpose Methods known.
  • an alternative is also an alternative explicit mapping between the output of the Object recognition system (2) and the control unit (7) by means of Machine models conceivable.
  • the control unit (8) serves to initiate actions, which reduce the risk of collision. If one of the the collision risk assessment unit (7) formed probability measures a certain Threshold is exceeded, by means of the control unit (8) one or more actions to reduce the Collision risk. It can be for example, to act as a horn signal, which others Road users warns. An acoustic signal in the vehicle inside is suitable to warn the driver, if this for example, in a collision hazard in another Direction as the vehicle ahead direction looks.
  • Fig. 2a shows a traffic scene wherein a pedestrian crosses a street. Due to his line of sight, it becomes clear that the pedestrian is attentive and notices the approaching vehicle.
  • Fig. 3a shows a scene in which a pedestrian crosses a street, which must be assumed due to the viewing direction that this has not noticed the approaching vehicle.
  • the road users are clearly recognizable and shown sufficiently large to be able to recognize the line of sight.
  • Commercially available low-resolution cameras with 320x240 pixels are generally sufficient for use in connection with road vehicles. Using one of S. Baker and T. Kanade, "Limits on Super-Resolution and How to Break Them," IEEE Trans. On Pattern Analysis and Machine Intelligence, vol. 24, no. 9, 2000 known algorithm, an increase in the recognition distance is achieved.
  • Figures 2b and 3b each show an enlarged image detail that shown in Figures 2a and 2b Traffic scenes, in which in particular in each case the head of recognized road user is depicted.
  • Fig. 2b keeps the road user direct eye contact Driver while that shown in Fig. 3b Road user keeps no eye contact with the driver.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
  • Image Processing (AREA)
  • Image Analysis (AREA)
EP04013002A 2003-06-05 2004-06-02 Système de traitement d'images pour un véhicule Withdrawn EP1486932A3 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE10325762 2003-06-05
DE10325762A DE10325762A1 (de) 2003-06-05 2003-06-05 Bildverarbeitungssystem für ein Fahrzeug

Publications (2)

Publication Number Publication Date
EP1486932A2 true EP1486932A2 (fr) 2004-12-15
EP1486932A3 EP1486932A3 (fr) 2005-11-02

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Family Applications (1)

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EP04013002A Withdrawn EP1486932A3 (fr) 2003-06-05 2004-06-02 Système de traitement d'images pour un véhicule

Country Status (4)

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US (1) US20040246114A1 (fr)
EP (1) EP1486932A3 (fr)
JP (1) JP2004362586A (fr)
DE (1) DE10325762A1 (fr)

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CN111614938A (zh) * 2020-05-14 2020-09-01 杭州海康威视系统技术有限公司 一种风险识别方法及装置
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WO2014118178A1 (fr) * 2013-01-30 2014-08-07 Bayerische Motoren Werke Aktiengesellschaft Établissement d'un modèle de l'environnement d'un véhicule
CN111614938A (zh) * 2020-05-14 2020-09-01 杭州海康威视系统技术有限公司 一种风险识别方法及装置
CN111614938B (zh) * 2020-05-14 2021-11-02 杭州海康威视系统技术有限公司 一种风险识别方法及装置

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EP1486932A3 (fr) 2005-11-02
JP2004362586A (ja) 2004-12-24
DE10325762A1 (de) 2004-12-23
US20040246114A1 (en) 2004-12-09

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