Method and apparatus for real-time distributed video analysis

• US 20070011711A1
• Filed: 06/26/2006
• Published: 01/11/2007
• Est. Priority Date: 06/24/2005
• Status: Abandoned Application

• Current Assignee: Changhong Lin, I Ozer, Tiehan Lv, Wayne Wolf
• Original Assignee: Changhong Lin, I Ozer, Tiehan Lv, Wayne Wolf
• Inventors: Wolf, Wayne, Lv, Tiehan, Ozer, I., Lin, Changhong
• Application Number:
  US11/474,848
• Publication Number:
  US 20070011711A1
• Time in Patent Office: Days
• US Class Current: 725/105
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
• CPC Class Codes: G06V 10/95 structured as a network, e.g. client-server architectures
• CPC Class Codes: G06V 20/00 Scenes; Scene-specific elements control of digital cameras H04N23/60
• CPC Class Codes: G06V 40/23 Recognition of whole body movements, e.g. for sport training

Abstract

The present invention describes a method and system for the real-time processing of video from multiple cameras using distributed computers using a peer-to-peer network, thus eliminating the need to send all video data to a centralized server for processing. The method and system use a distributed control algorithm to assign video processing tasks to a plurality of processors in the system. The present invention also describes automated techniques to calibrate the required parameters of the cameras in both time and space.

Claims

1. A system for analyzing a target scene, comprising:

a plurality of visual sensing nodes each comprising at least one visual sensing unit for capturing visual data relating to the target scene and an associated processor for intra-frame processing and inter-frame processing of the captured data to form at least one message; and

a peer-to-peer network communicatively connecting at least two of said visual sensing nodes to enable the at least one message from each node to be compared with each other to form an overall processing result.

2. The system of claim 1, further comprising at least one control signal by which the visual sensing nodes cooperate to determine which visual sensing nodes will be responsible for forming which parts of the overall processing result.

3. The system of claim 1, wherein the plurality of visual sensing nodes are smart cameras.

4. The system of claim 1, wherein the at least one visual sensing unit is a camera.

5. The system of claim 1, wherein the intra-frame processing operation utilizes a pixel-based algorithm.

6. The system of claim 1, wherein the intra-frame processing operation utilizes a compressed-domain algorithm.

7. The system of claim 1, wherein the intra-frame processing includes the steps of region segmentation, contour following, ellipse fitting and graph matching.

8. The system of claim 1, wherein the at least one processing result is distributed among the plurality of visual sensing nodes in response to an overlap among the at least one processing result of the plurality of visual sensing nodes.

9. The system of claim 8, wherein the each of the plurality of visual sensing nodes merges the at least one processing result from other of the plurality of visual sensing nodes with its own at least one processing result.

10. The system of claim 1, wherein the inter-frame processing further comprises the sub-steps of (a) applying hidden Markov models in parallel to generate code words representing gestures of at least one object and (b) using the code words to communicate information regarding the gestures of the at least one object to the output.

11. A method for analyzing a target scene, comprising

capturing visual data via a plurality of visual sensing nodes;

performing at least one intra-frame processing operation and at least one inter-frame processing operation on the visual data to form at least one message;

distributing, via a peer-to-peer network, the at least one message among the plurality of visual sensing nodes to be compared with each other to form an overall processing result.

12. The method of claim 11, wherein the visual sensing nodes cooperate to determine which visual sensing nodes will be responsible for forming which parts of the overall processing result via at least one control signal.

13. The method of claim 12, wherein the one or more mechanisms are control signals.

14. The method of claim 11, wherein plurality of visual sensing nodes are smart cameras.

15. The method of claim 11, wherein the at least one visual sensing unit is a camera.

16. The method of claim 11, wherein the intra-frame processing operation utilizes a pixel-based algorithm.

17. The method of claim 11, wherein the intra-frame processing utilizes a compressed-domain algorithm.

18. The method of claim 11, wherein the intra-frame processing includes the steps of region segmentation, contour following, ellipse fitting, and graph matching.

19. The method of claim 11, wherein the at least one processing result is distributed among the plurality of visual sensing nodes in response to an overlap among the at least one processing result of the plurality of visual sensing nodes.

20. The method of claim 11, wherein the each of the plurality of visual sensing nodes merges the at least one processing result from other of the plurality of visual sensing nodes with its own at least one processing result.

21. The method of claim 11, wherein the inter-frame operation further comprises the sub-steps of (a) applying hidden Markov models in parallel to generate code words representing gestures of at least one object and (b) using the code words to communicate information regarding the gestures of the at least one object to the output.