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WO2009108039A2 - Procédé de détection d’événements anormaux pour des images vidéo à grand angle - Google Patents

Procédé de détection d’événements anormaux pour des images vidéo à grand angle Download PDF

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Publication number
WO2009108039A2
WO2009108039A2 PCT/MY2009/000035 MY2009000035W WO2009108039A2 WO 2009108039 A2 WO2009108039 A2 WO 2009108039A2 MY 2009000035 W MY2009000035 W MY 2009000035W WO 2009108039 A2 WO2009108039 A2 WO 2009108039A2
Authority
WO
WIPO (PCT)
Prior art keywords
multiclassifier
classifier
during
wide view
phase
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/MY2009/000035
Other languages
English (en)
Other versions
WO2009108039A3 (fr
Inventor
Kim Meng Liang
Tomas Henrique Maul
Chen Change Loy
Zulaikha Kadim
Chue Poh Tan
Ahmed Abd. Bahaa Al-Deen
Weng Kin Lai
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.)
Mimos Bhd
Original Assignee
Mimos Bhd
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 Mimos Bhd filed Critical Mimos Bhd
Publication of WO2009108039A2 publication Critical patent/WO2009108039A2/fr
Publication of WO2009108039A3 publication Critical patent/WO2009108039A3/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H04N5/2628—Alteration of picture size, shape, position or orientation, e.g. zooming, rotation, rolling, perspective, translation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/254—Analysis of motion involving subtraction of images
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR 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
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19617—Surveillance camera constructional details
    • G08B13/19626—Surveillance camera constructional details optical details, e.g. lenses, mirrors or multiple lenses
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR 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
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19617—Surveillance camera constructional details
    • G08B13/19626—Surveillance camera constructional details optical details, e.g. lenses, mirrors or multiple lenses
    • G08B13/19628—Surveillance camera constructional details optical details, e.g. lenses, mirrors or multiple lenses of wide angled cameras and camera groups, e.g. omni-directional cameras, fish eye, single units having multiple cameras achieving a wide angle view
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/698—Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30232—Surveillance

Definitions

  • the present invention relates in general to a method to detect abnormal events in images captured by wide view camera through behavioral analysis; and more particularly in dealing with spatial distortion in the video images.
  • the surveillance camera In automated video surveillance an event is classified as normal or abnormal based on predetermined condition(s) and is displayed automatically in real time. This would then enable the security personnel to take the necessary action. Therefore, there is a need for the surveillance camera to be able to circumscribe as wide an area as possible with the least number of cameras.
  • wide view cameras i.e. video cameras with wide-angle lens are used.
  • Wide view camera is able to increase the field of view to up to 225°. This is very useful in achieving a wide coverage, however it is at the expense of the quality of the images acquired.
  • the images have barrel distortion, whereby the image looks like it has been formed around a sphere. Typically, the greater the field of view the greater the distortion, and the more curved straight lines appear.
  • the object of this invention is to provide a method to detect abnormal event in systems using wide view images.
  • Another objective of the invention is to provide a system which incorporates image distortion handling strategies as opposed to image distortion correction pre-process.
  • Figure 1 illustrates a flow chart of a conventional abnormal event system overview.
  • Live video images of an area of interest for example the area where surveillance is conducted is obtained through image acquisition devices such as surveillance camera(s) coupled wide view lens such as fish eye lens.
  • image acquisition devices such as surveillance camera(s) coupled wide view lens such as fish eye lens.
  • the images from this type of camera are severely distorted as shown in Figure 1.
  • the images acquired are pre-processed to correct the spatial distortion caused by the lens. This result is then used as the input for the abnormal event analyzer.
  • Figure 3 illustrates a flow chart of an abnormal event detection system according to the present invention.
  • the images for the present invention are also obtained from a conventional wide view vide acquisition device, it does not require pre-processing step where the images are corrected of their spatial distortion.
  • the present invention successfully eliminates the image distortion correction by incorporating image distortion handling strategies at the level of a multi-classifier, namely: during training, classification and fusion.
  • the main essence of this approach is to make the multi classifier savvy of the distortion geometry of the data that it is processing.
  • the invention incorporates distortion geometry prior knowledge in three different instances: a. During the training of the multi classifier b. During the execution of the multi classifier c. During the fusion of the multi classifier outputs
  • Figure 6 illustrates how a multiple classifier can be used in the context of a wide view image.
  • the figure on the right indicates an actual wide view image.
  • the image can be broken into two or more geometric bands. However, for the purpose of discussion the number of bands is limited to three as can be seen in Figure 6.
  • the distortion parameters within a band are sufficiently similar, whereas the distortion parameters between the bands are sufficiently dissimilar.
  • Each geometric band is assigned with a classifier and each classifier region overlaps with an adjacent classifier region in order to smoothen the output of the fusion process.
  • the number and configurations of the classifiers are determined by the distortion characteristics of the image.
  • each classifier is assigned to a specific band or region with similar distortion parameters. Although the distortion parameters within a band are similar, there still exists a certain margin of variability. Therefore, during the training phase the classifier is trained with a distortion pattern that corresponds to a target object at a specific coordinate/position and also with a range of possible variables of that distortion pattern.
  • the variations of distortion parameters associated with various objects at different positions are the data with which the classifier will be trained on. These data may vary depending on the various applications of the system. For example the data for training a classifier for a surveillance system in an airport would not be the same as for a classifier for a surveillance system in a bookstore.
  • the classifier which has access to a target object's position is able to retrieve the distortion parameters which are associated with that particular ⁇ position, from the data stored during the training phase. This allows the classifier to adapt its functions to be optimized for that set of parameters.
  • the classifier compares the distorted images obtained with those stored in the database during the training phase. The result from this is used as input for the fusion phase.
  • any automated surveillance is trained to compare the real time events to events in a database to in order to determine if an abnormal event has occurred.
  • normal events consists of events that are expected to happen at a certain area of interest where the surveillance system is being employed.
  • Figure 4 indicates the process for generation of abnormal events for storage for the present invention.
  • Live wide view video images are received from the acquisition device and the image data received is processed with data processor such as an ordinary computer.
  • the image data is first processed in the illumination analysis component to recover the true pigmentation information of the images.
  • the background and foreground of the area of interest is then identified through foreground detection.
  • Once the key objects in the area of interest is known the various segments of these objects will be partitioned into the appropriate number of region so as to simplify and/or change the representation of the image into something that is more meaningful and easier to understand.
  • the result of this step will be further processed to identify and select the key features of the object for event analysis and tracking.
  • the behavioral characteristics as well as other important details will be classified through the context sensitive multi classifier before being labeled and stored into the events database.
  • the system can be used in real time abnormal event detection.
  • the abnormal event detection process is very much similar to that of the generation of abnormal event for storage.

Landscapes

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

Abstract

La présente invention concerne un procédé de détection d’un événement anormal dans un système de surveillance utilisant des images vidéo à grand angle. Plus particulièrement, la présente invention fournit une solution pour éliminer les distorsions d’images qui sont associées à des images vidéo à grand angle.
PCT/MY2009/000035 2008-02-27 2009-02-27 Procédé de détection d’événements anormaux pour des images vidéo à grand angle Ceased WO2009108039A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
MYPI20080419 2008-02-27
MYPI20080419A MY144955A (en) 2008-02-27 2008-02-27 Method to detect abnormal events for wide view video images

Publications (2)

Publication Number Publication Date
WO2009108039A2 true WO2009108039A2 (fr) 2009-09-03
WO2009108039A3 WO2009108039A3 (fr) 2009-10-22

Family

ID=41016618

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/MY2009/000035 Ceased WO2009108039A2 (fr) 2008-02-27 2009-02-27 Procédé de détection d’événements anormaux pour des images vidéo à grand angle

Country Status (2)

Country Link
MY (1) MY144955A (fr)
WO (1) WO2009108039A2 (fr)

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7940299B2 (en) * 2001-08-09 2011-05-10 Technest Holdings, Inc. Method and apparatus for an omni-directional video surveillance system
US7336299B2 (en) * 2003-07-03 2008-02-26 Physical Optics Corporation Panoramic video system with real-time distortion-free imaging
US7576767B2 (en) * 2004-07-26 2009-08-18 Geo Semiconductors Inc. Panoramic vision system and method

Also Published As

Publication number Publication date
MY144955A (en) 2011-11-30
WO2009108039A3 (fr) 2009-10-22

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