EP2174260A2 - Dispositif pour identifier et/ou classifier des modèles de mouvements dans une séquence d'images d'une scène de surveillance, procédé et programme informatique - Google Patents

Dispositif pour identifier et/ou classifier des modèles de mouvements dans une séquence d'images d'une scène de surveillance, procédé et programme informatique

Info

Publication number
EP2174260A2
EP2174260A2 EP08760696A EP08760696A EP2174260A2 EP 2174260 A2 EP2174260 A2 EP 2174260A2 EP 08760696 A EP08760696 A EP 08760696A EP 08760696 A EP08760696 A EP 08760696A EP 2174260 A2 EP2174260 A2 EP 2174260A2
Authority
EP
European Patent Office
Prior art keywords
movement pattern
image sequence
pattern
patterns
surveillance
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Withdrawn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
EP08760696A
Other languages
German (de)
English (en)
Inventor
Julia Ebling
Hartmut Loos
Matthias Koenig
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.)
Robert Bosch GmbH
Original Assignee
Robert Bosch GmbH
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 Robert Bosch GmbH filed Critical Robert Bosch GmbH
Publication of EP2174260A2 publication Critical patent/EP2174260A2/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion

Definitions

  • the invention relates to a device for detecting and / or classifying movement patterns in an image sequence from a surveillance scene, wherein the
  • the Device has an interface for recording the image sequence and a calculation module for determining an optical flow field in the surveillance scene by evaluating the image sequence. Furthermore, the invention relates to a corresponding method and a computer program.
  • Video surveillance systems are used, for example, to monitor public places, railway stations, roads, industrial plants, buildings or the like.
  • the video surveillance systems usually comprise one or more surveillance cameras, which are aligned to surveillance scenes and transmit image data streams in the form of image sequences to an evaluation center. While it was common in the past, the
  • An often practiced approach to detecting and / or classifying motion patterns in surveillance scenes is to separate moving objects from the (essentially static) scene background, track over time, and raise alarms for relevant movements.
  • the methods used in the The first step for the so-called object segmentation is typically the image differences between the current camera image and a so-called scene reference image that models the static scene background to detect moving objects.
  • Another approach analyzes the so-called optical flow in the surveillance scene by evaluating the image sequence.
  • the translational movements of pixels or image regions are evaluated from an image to a subsequent image of the image sequence and a vector field is created on the basis of these translational movements, which respectively provides a translational direction and a translation speed for the examined pixels or regions.
  • an object segmentation is performed by classifying objects that correspond in terms of the translation vectors, that is to say with regard to the optical flow, to a common object.
  • a device for detecting and / or classifying movement patterns in a sequence of images from a surveillance scene with the features of claim 1 a corresponding method with the features of
  • the device according to the invention is characterized in particular in that the movement patterns are not necessarily recognized and classified via the intermediate path of object segmentation and subsequent object tracking, but rather that the optical flow field itself is based on characteristic movement patterns by comparison with predetermined ones and / or predeterminable patterns, in particular flow masks. While a single object approach is thus pursued in the prior art, the invention proposes a multiobject approach which simultaneously analyzes all moving objects in the surveillance scene and / or in a subarea of the surveillance scene.
  • the device is preferably designed as a video surveillance system, which is implemented, for example, as a data processing device, computer, DSP, microcontroller, FPGA, ASIC or the like and / or has one or more interfaces for recording image sequences of one or more surveillance scenes.
  • the interfaces are with a plurality of cameras,
  • the inventive device is particularly suitable due to a comparatively low computing power requirement for real-time use, but can also analyze already stored image sequences in particular "off-line".
  • the surveillance scene can - as already shown in the introduction - be designed as a street scene, intersection, public building, station, etc.
  • the surveillance scene shows a plurality of moving objects, particularly human, e.g. Passers-by, but can also be designed as vehicles or the like.
  • the image sequence comprises a plurality of in particular temporally equidistantly recorded images of the surveillance scene, wherein the images may have any specification, such as color, grayscale, black and white, infrared and / or UV image are realized.
  • the device has a calculation module, which is formed by program technology and / or circuitry for determining an optical flow field in the surveillance scene by evaluating the image sequence.
  • the optical flow field - also called optical flow - can be represented as a vector field having the preferably two-dimensional direction of movement and / or movement speed for each or every pixel selected, for each or each selected pixel, and / or for each or each selected one
  • the calculation of the optical flow field can be done by differential methods, but also by any other known method.
  • the device has a recognition module, which is designed in terms of programming and / or circuitry, to compare the optical flow field and / or subregions thereof with one or more patterns in order to recognize a movement pattern in the image sequence.
  • the recognition of the movement pattern takes place without the intermediate steps of object segmentation and tracking, so that on the one hand inaccuracies in the analysis can be avoided and, on the other, computer time can be saved.
  • the proposed invention thus uses the information obtained by calculating the
  • Movement can be obtained from small image areas, where an image area can also consist of a single pixel.
  • an image area can also consist of a single pixel.
  • the evolution of the flow fields over time is also considered.
  • Another useful advantage of the invention is that the underlying method is applicable, even if there are so many moving objects in the surveillance scene that they overlap, merge and / or that one another object segmentation, e.g. via a scene reference image is not or no longer possible with the necessary reliability.
  • the invention allows the detection of motion patterns in the image sequences even in overcrowded surveillance scenes.
  • the invention is suitable for detecting movement patterns that are based on mass psychological and / or group dynamic behavior, that is to say in particular on the joint behavior of large ones
  • the movement pattern is formed as a global movement pattern which reflects the movement throughout
  • This embodiment is particularly suitable when the surveillance scene shows a crowd and a common behavior of the people in the crowd is to be classified through the analysis of the movement pattern.
  • the movement pattern is designed as a local movement pattern describing the movement in a subarea of the surveillance scene.
  • the subarea may be set by a user in one possible alternative embodiment, such that, for example, one escalator is selected as a subarea or another Alternatively, alternative embodiments can be determined automatically, for example by selecting subregions in which more object movements are detected than other subregions of the surveillance scene. However, it is preferred that the sub-region of the surveillance scenes comprise a plurality of moving objects in order to best exploit the advantages of the invention.
  • the device has a classification module which, taking into account the detected movement pattern or patterns of the surveillance scenes, assigns a monitoring situation.
  • the device according to the invention undergoes an application-specific expression in that the
  • Monitoring scene is assigned as a real surveillance scene a real monitoring situation.
  • real monitoring situations can be configured as desired, for example as a human snake, a regularly traveled road, a purpose-used roundabout, etc .
  • the invention is suitable real monitoring situations, preferably dangerous situations such as fallen persons, escape behavior, panic and situations which attract onlookers, especially in overcrowded surveillance scenes automatically detect and trigger a reaction, such as the transmission of an alarm call.
  • the classification module has an arbitrary selection of the following assignments:
  • a movement pattern with flux lines directed at a common point is assigned to the monitoring situation "gathering."
  • a monitoring situation arises, for example, when approaching moving objects, in particular people or onlookers, to a common center.
  • a movement pattern with flux lines directed away from a common point, ie a divergence, is assigned to the monitoring situation "scattering."
  • a monitoring situation is created when moving objects flow apart, for example when a person escapes from a central point.
  • a movement pattern with flux lines running around a common point is assigned to the "avoidance" monitoring situation and is an example of one Monitoring situation, wherein the surveillance scene has an obstacle, which is bypassed by the moving objects.
  • Calculation module designed to determine statistical characteristics of the optical flow field. This embodiment is particularly useful when no structure or motion model is detectable in an optical flow field.
  • the determination of statistical parameters checks whether the surveillance scene can be assigned to the chaos or panic monitoring situation. Even with recognized movement patterns, the device is preferably designed so that the detected movement patterns are confirmed or verizif ⁇ extend with statistical or other characteristics.
  • the pattern is designed as a two- or three-dimensional data field. It may be provided that the size of the pattern corresponds to the size of an image of the image sequence. Alternatively, it may be provided that the size of the pattern is limited to the size of a subarea, in particular of the subarea of the image to be examined, and thus to the relevant surveillance scene. In one possible alternative, the pattern is as
  • Window formed with the optical flow field for example sliding, is traversed.
  • the movement pattern is detected by applying a classification method.
  • a classification method In such a
  • the optical flow field is compared with a first pattern in a first classification stage, with a second pattern in a second classification stage and with an nth pattern in an nth classification stage.
  • a movement pattern is thus recognized by a plurality of positively classified individual patterns. For example, to save computation time, it may be provided that once a pattern of a classification stage can not be found in the optical flow field, this pattern is discarded.
  • the classification method is designed as a classification tree, wherein the branches of the tree are formed by classification stages.
  • the movement pattern is recognized on the basis of a plurality of found patterns.
  • the assignment of the multiple patterns to a movement pattern can be implemented, for example, automatically by a learning process.
  • the patterns are formed as linear, shift-invariant patterns and / or the pattern matching is implemented via clifford convolution.
  • Another object of the invention relates to a method for detecting and / or classification of a movement pattern or in an image sequence of one or the surveillance scene with the features of claim 12, which is preferably carried out on the device just described or on the device according to the preceding claims becomes.
  • the optical flow field in the image sequence of the surveillance scene is calculated and in a second step the optical flow field is compared with one or more patterns in order to detect one or the movement pattern in the image sequence or in the surveillance scene.
  • Another optional step is to assign a monitoring situation to the detected movement pattern.
  • Figure 1 is a block diagram of a video surveillance system as a first embodiment of the invention
  • Figure 2 is a schematic representation as a first example of an optical
  • Figure 3 is a schematic representation as a second example of an optical
  • Figure 4 is a schematic representation as a third example of an optical
  • Figure 5 is a schematic representation as a fourth example of an optical flow field with a fourth movement pattern.
  • FIG. 1 shows a schematic block diagram of a video surveillance system
  • the video surveillance system 1 is connected via an interface 2 with one or more
  • the surveillance cameras 3 are positioned to monitor the said surveillance scenes and direct the image data stream either first for caching in the video recorder or 4 or directly in the video surveillance system.
  • the image data streams which correspond to image sequences of the surveillance scene, are first transferred to a calculation module 5.
  • the calculation module 5 is program-technically and / or circuit-wise designed to generate an optical flow field or a time-varying optical flow field from an image sequence of a surveillance scene.
  • the flow field is created for the translational movements of pixels or image regions in the images of the image sequence over at least two and preferably more than ten images. It can also be provided that the optical flow field is generated in a manner that is virtually sliding for the image sequence, in that in each case the oldest image from the calculation for the optical flow field is calculated for the calculation of the current optical flow field
  • Flow field is removed and replaced by the latest image of the image sequence (FiFo).
  • the generated optical flow field is passed to a recognition module 6, which is designed to compare the optical flow field with patterns or pattern masks from a pattern memory 7, wherein the patterns in the pattern memory 7 are designed such that movement patterns in the image sequence or in the surveillance scene can be recognized.
  • the patterns in the pattern memory 7 can be designed as two- or three-dimensional data fields and have a size that is similar in size to an image of the image sequence or as a subregion of an image of the image sequence.
  • a single pattern from the pattern memory 7 may be applied to the optical flow field, alternatively, multiple patterns from the pattern memory 7 are applied to the optical flow field and the motion pattern is recognized by classification procedures, decision trees, etc.
  • a movement pattern After a movement pattern has been detected, it is transferred to a classification module 8, wherein the classification module 8 is designed to assign the detected movement pattern to a specific real monitoring situation, such as flight, confluence, chaos, panic, etc. As soon as the assignment of the movement pattern to the monitoring situation has been completed, a message can optionally be sent to a monitoring personnel via a notification module 9.
  • a classification module 8 is designed to assign the detected movement pattern to a specific real monitoring situation, such as flight, confluence, chaos, panic, etc.
  • the process running on the video surveillance system 1 thus comprises the steps of accepting images or image sequences of a surveillance scene, which Calculation of the optical flow field for the current image of the image sequence, optionally temporal filtering of the optical flow field to suppress interference and the determination of monitoring situations on the comparison of the optical flow fields or with predetermined flow masks or patterns that describe typical movement patterns, an analysis of calculated similarities, optionally a statistical analysis of the directions of movement for further information and to secure the results and finally the classification of the monitoring situation, where appropriate for different image areas.
  • FIG. 2 shows in a highly schematized representation a first example of an optical flow field 10 with a movement pattern such as occurs during the influx of persons, such as onlookers.
  • a movement pattern such as occurs during the influx of persons, such as onlookers.
  • all or most of the motion vectors 11 are directed to a common center 12, so that this movement pattern can be easily recognized automatically by the recognition module 6.
  • the movement pattern may be referred to as a convergent movement pattern.
  • the movement pattern recognized by the recognition module 6 is then reported to the classification module 8, which assigns to this convergent movement pattern the monitoring situation "oncoming persons.”
  • the classification module 8 assigns to this convergent movement pattern the monitoring situation "oncoming persons.”
  • FIG. 3 shows a second exemplary embodiment of a schematic optical system
  • Flow field 10 which has a movement pattern that corresponds to the flow of people, such as happens when escaping. All or most of the flow vectors 11 are star-shaped away from the common center 12 in this embodiment.
  • the recognition module 6 will recognize this movement pattern, for example, as a divergent movement pattern and to the
  • FIG. 4 shows a third example of an optical flow field 10, this third example showing the movement pattern of persons circulating an obstacle.
  • two flows are produced for the flow vectors 11, wherein the flow arranged on the left side of FIG. 4 runs from top to bottom and the flow arranged on the right side runs from bottom to top.
  • the common center 12 is bypassed by both streams.
  • FIG. 5 shows a last exemplary embodiment of an optical flow field 10, wherein the flow vectors 11 have no uniform direction and no common center can be detected.
  • a movement pattern which may be denoted as a chaotic movement pattern, or the message that no movement pattern was found
  • the classification module 8 will assume a panic situation as a monitoring situation and also activate the notification module 9.
  • a video-based surveillance system is presented with the invention, which can be used for the observation of complete scenarios, and it is particularly suitable for the observation of dangerous situations in crowded scenes, ie in scenes in which move many moving objects.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Image Analysis (AREA)
  • Closed-Circuit Television Systems (AREA)

Abstract

Des systèmes de vidéosurveillance servent, par exemple, à surveiller des lieux publics, des gares, des rues, des installations industrielles, des bâtiments ou des objets similaires. Les systèmes de vidéosurveillance comprennent la plupart du temps une ou plusieurs caméras de surveillance qui sont orientées vers des scènes de surveillance et transmettent des flux de données images sous forme de séquences d'images à un centre d'analyse. L'invention concerne un dispositif (1) pour identifier et/ou classifier un modèle de mouvements dans une séquence d'images d'une scène de surveillance présentant une pluralité d'objets en mouvement, ce dispositif comportant une interface (2) destinée à la visualisation de la séquence d'images, un module de calcul (5) pour déterminer un flux optique (10) dans la scène de surveillance par analyse de la séquence d'images, et un module d'identification (6) techniquement conçu en termes de programme et de circuit pour comparer le flux optique et/ou des zones partielles de celui-ci à un ou plusieurs modèles afin d'identifier le modèle de mouvements dans la séquence d'images.
EP08760696A 2007-07-05 2008-06-06 Dispositif pour identifier et/ou classifier des modèles de mouvements dans une séquence d'images d'une scène de surveillance, procédé et programme informatique Withdrawn EP2174260A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102007031302A DE102007031302A1 (de) 2007-07-05 2007-07-05 Vorrichtung zur Erkennung und/oder Klassifizierung von Bewegungsmustern in einer Bildsequenz von einer Überwachungsszene, Verfahren sowie Computerprogramm
PCT/EP2008/057127 WO2009003793A2 (fr) 2007-07-05 2008-06-06 Dispositif pour identifier et/ou classifier des modèles de mouvements dans une séquence d'images d'une scène de surveillance, procédé et programme informatique

Publications (1)

Publication Number Publication Date
EP2174260A2 true EP2174260A2 (fr) 2010-04-14

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EP08760696A Withdrawn EP2174260A2 (fr) 2007-07-05 2008-06-06 Dispositif pour identifier et/ou classifier des modèles de mouvements dans une séquence d'images d'une scène de surveillance, procédé et programme informatique

Country Status (4)

Country Link
US (1) US8761436B2 (fr)
EP (1) EP2174260A2 (fr)
DE (1) DE102007031302A1 (fr)
WO (1) WO2009003793A2 (fr)

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102009000173A1 (de) * 2009-01-13 2010-07-15 Robert Bosch Gmbh Vorrichtung zum Zählen von Objekten, Verfahren sowie Computerprogramm
US9361706B2 (en) * 2009-11-30 2016-06-07 Brigham Young University Real-time optical flow sensor design and its application to obstacle detection
US20110157355A1 (en) * 2009-12-28 2011-06-30 Yuri Ivanov Method and System for Detecting Events in Environments
US20120019727A1 (en) * 2010-07-21 2012-01-26 Fan Zhai Efficient Motion-Adaptive Noise Reduction Scheme for Video Signals
JP5776769B2 (ja) * 2011-05-24 2015-09-09 富士通株式会社 物体接近検知装置、物体接近検知方法、及びプログラム
RU2015147449A (ru) * 2013-04-19 2017-05-24 Джеймс КАРЕЙ Аналитическая система распознавания и видеоидентификации
DE102016210056A1 (de) 2016-06-08 2017-12-14 Robert Bosch Gmbh Kameraanordnung zur Bestimmung des optischen Flusses, Fahrassistenzsystem und Überwachungskamera mit der Kameraanordnung
DE102016211049A1 (de) * 2016-06-21 2017-12-21 Siemens Aktiengesellschaft Verfahren und Vorrichtung zum eine Vorrichtung und ein Verfahren zur Ausgabe wenigstens eines Alarmsignals
DE102017222898A1 (de) * 2017-12-15 2019-06-19 Siemens Aktiengesellschaft Automatisiertes Detektieren von Gefahrensituationen
DE102018108204B4 (de) 2018-04-06 2023-07-27 Rheinmetall Air Defence Ag Interventionssystem zur Abwehr eines Schwarms von unbemannten Flugkörpern und Verfahren zur Abwehr eines Schwarms von unbemannten Flugkörpern mittels eines solchen Interventionssystems
EP3852521A1 (fr) * 2018-09-21 2021-07-28 Bayer Aktiengesellschaft Observation d'arthropodes assistée par capteur
CN115063482A (zh) * 2019-11-21 2022-09-16 奇购视觉有限公司 物品识别及追踪方法与系统
US11580833B2 (en) * 2020-03-24 2023-02-14 Object Video Labs, LLC Camera detection of human activity with co-occurrence
CN112633100B (zh) * 2020-12-14 2023-08-08 深兰人工智能应用研究院(山东)有限公司 行为识别方法、装置、电子设备和存储介质
US11388555B1 (en) 2020-12-30 2022-07-12 Here Global B.V. Method, apparatus, and computer program product for quantifying human mobility
DE102021206914A1 (de) * 2021-07-01 2023-01-05 Siemens Mobility GmbH Verfahren zum Erkennen eines sicherheitsrelevanten Ereignisses innerhalb einer Fahrgastkabine eines Schienenfahrzeugs

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6628715B1 (en) * 1999-01-15 2003-09-30 Digital Video Express, L.P. Method and apparatus for estimating optical flow
US7123745B1 (en) * 1999-11-24 2006-10-17 Koninklijke Philips Electronics N.V. Method and apparatus for detecting moving objects in video conferencing and other applications
US7266220B2 (en) * 2002-05-09 2007-09-04 Matsushita Electric Industrial Co., Ltd. Monitoring device, monitoring method and program for monitoring
KR100630088B1 (ko) * 2004-12-28 2006-09-27 삼성전자주식회사 옵티컬 플로우를 이용한 차량 감시 장치 및 방법
US7646887B2 (en) * 2005-01-04 2010-01-12 Evolution Robotics Retail, Inc. Optical flow for object recognition
DE102006053286A1 (de) * 2006-11-13 2008-05-15 Robert Bosch Gmbh Verfahren zur Detektion von bewegungsauffälligen Bildbereichen, Vorrichtung sowie Computerprogramm zur Durchführung des Verfahrens

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO2009003793A2 *

Also Published As

Publication number Publication date
DE102007031302A1 (de) 2009-01-08
US20100177936A1 (en) 2010-07-15
WO2009003793A2 (fr) 2009-01-08
WO2009003793A3 (fr) 2009-05-14
US8761436B2 (en) 2014-06-24

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