Method and apparatus for computerized image background analysis

• US 7,221,775 B2
• Filed: 09/10/2003
• Issued: 05/22/2007
• Est. Priority Date: 11/12/2002
• Status: Active Grant

• Current Assignee: Johnson Controls Tyco IP Holdings LLP (Johnson Controls International plc)
• Original Assignee: Intellivid Corporation (Johnson Controls International plc)
• Inventors: Buehler, Christopher J.
• Primary Examiner(s): SHERALI, ISHRAT I
• Application Number:
  US10/659,454
• Publication Number:
  US 20040119848A1
• Time in Patent Office: 1,350 Days
• Field of Search: 382/100, 382/103, 382/107, 382/173, 382224-227, 382/180, 382/104, 382/154, 348169-172, 348143-159, 348/200, 348/208.1, 348/207.1, 340/522, 340/572.1, 356/612, 342 90- 96, 715/700, 725/105, 725/561, 725/534, 702/188, 701/207, 706/16, 700/48
• US Class Current: 382/100
• CPC Class Codes: G06T 7/254 involving subtraction of images
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G08B 13/19602 Image analysis to detect motion of the intruder, e.g. by frame subtraction
• CPC Class Codes: G08B 13/19604 involving reference image or background adaptation with time to compensate for changing conditions, e.g. reference image update on detection of light level change
• CPC Class Codes: G08B 13/19608 Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position
• CPC Class Codes: G08B 13/19641 Multiple cameras having overlapping views on a single scene
• CPC Class Codes: G08B 13/19652 Systems using zones in a single scene defined for different treatment, e.g. outer zone gives pre-alarm, inner zone gives alarm
• CPC Class Codes: G08B 13/19656 Network used to communicate with a camera, e.g. WAN, LAN, Internet
• CPC Class Codes: G08B 13/246 Check out systems combined with EAS, e.g. price information stored on EAS tag anti-theft systems in point of sale systems G07G3/003
• CPC Class Codes: H04N 5/272 Means for inserting a foreground image in a background image, i.e. inlay, outlay
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

A computerized method of video analysis including receiving image data for a plurality of video frames depicting a scene that includes at least one of a plurality of background features. Each video frame includes a plurality of image regions and at least one video frame has an object within at least one of the image region. A plurality of background classifications is provided that correspond to one of the background features in the scene. At least one image region is assigned a background classification based at least in part on the location of the object relative to the image region.

Claims

1. A computerized method of video analysis, the method comprising:

receiving image data for a plurality of video frames depicting a scene that includes at least one of a plurality of background features, wherein (i) each of the video frames comprises a plurality of image regions and (ii) at least one video frame has an object within at least one image region;

providing a plurality of background classifications each corresponding to one of the background features in the scene;

comparing a value associated with the image regions to a background-specific threshold; and

assigning one of the background classifications to at least one of the image regions based at least in part on a location of the object relative to the image regions and the comparison.

2. The method of claim 1 wherein one of the background classifications is a floor.

3. The method of claim 1 wherein the background-specific threshold comprises a floor threshold.

4. The method of claim 1 wherein one of the background classifications is an obstruction.

5. The method of claim 1 wherein the assigning of a background classification to an image region further comprises:

comparing a value associated with the image region to a background-specific threshold; and

comparing a value associated with the image region to an obstruction threshold.

6. The method of claim 1 wherein one of the background classifications is a portal.

7. The method of claim 1 further comprising:

determining for each video frame whether an object has newly appeared in such video frame; and

determining the image regions in which the newly appeared objects are present.

8. The method of claim 7 wherein the assigning of a background classification to an image region further comprises counting the number of newly appeared objects that first appeared in the image region.

9. The method of claim 1 further comprising:

determining for each video frame whether an object has newly disappeared in such video frame; and

determining the image regions in which the newly disappeared objects were last present in a previous video frame.

10. The method of claim 9 wherein the assigning of a background classification to an image region further comprises counting the number of disappeared objects that disappeared from the image region.

11. The method of claim 1 further comprising determining whether to track the object based at least in part on the background classification assigned to at least one of the image regions of the video frame.

12. The method of claim 1 wherein the object further comprises a boundary, the method further comprising the step of determining at least one boundary region that includes the boundary of the object.

13. The method of claim 1 wherein the object further comprises a boundary, the method further comprising the step of determining at least one boundary region that includes at least one of the top, bottom, and side boundaries of the object.

14. The method of claim 13 further comprising determining whether to track the object based at least in part on the image regions in which the at least one boundary region is included relative to the background classification assigned to at least one of (i) such image regions and (ii) another image region in the video frame.

15. The method of claim 1 further comprising determining whether to track the object based at least in part on the size of the object.

16. The method of claim 1 further comprising determining whether to track the object based at least in part on (i) the size of the object and (ii) the image regions in which the object is present relative to the background classification assigned to at least one of (a) such image regions and (b) another image region.

17. The method of claim 1 further comprising:

selecting one of the video frames that has an object; and

determining whether the object appears in one of the other video frames based at least in part on the background classification assigned to one of the image regions.

18. The method of claim 1 further comprising:

selecting one of the video frames that has an object; and

determining whether the object appears in one of the other video frames at one of an earlier and later time based on the background classification assigned to one of the image regions.

19. A video analysis system comprising:

means for receiving image data for a plurality of video frames depicting a scene that includes at least one of a plurality of background features, wherein (i) each of the video frames comprises a plurality of image regions and (ii) at least one video frame has an object within at least one image region;

means for providing a plurality of background classifications each corresponding to one of the background features in the scene;

means for comparing a value associated with the image regions to a background-specific threshold; and

means for assigning one of the background classifications to at least one of the image regions based at least in part on a location of the object relative to the image regions and the results of the comparison.