Method And Apparatus For Adaptive Object Detection

• US 20090129629A1
• Filed: 01/18/2008
• Published: 05/21/2009
• Est. Priority Date: 11/21/2007
• Status: Abandoned Application

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Wang, Wen-Hao, Cheng, Po-Feng
• Application Number:
  US12/016,207
• Publication Number:
  US 20090129629A1
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: G06V 40/162 using pixel segmentation or colour matching

Abstract

Disclosed is a method and apparatus for adaptive object detection, which may be applied in detecting an object having an ellipse feature. The method for adaptive object detection comprises performing an object shape detection based on the extracted foreground from the object; determining whether the object being occluded according to the detected feature statistic information of the object; if the object being not occluded, determining whether to switching object shape detection to ellipse detection; if the object being occluded or necessary to switch to ellipse detection, performing ellipse detection on the foreground; when the foreground being detected to have ellipse features, the object is continuously tracked; and when the current detection being ellipse detection, determining whether the ellipse detection being able to switch back to object shape detection.

Claims

1. A method for adaptive object detection, applicable to the detection of an object with an ellipse feature, said method comprising:

performing object shape detection on said object, based on an extracted foreground of said object;

according to the feature statistic information of said detected object, determining whether said object being occluded;

if said object not being occluded, determining whether to switch from object shape detection to ellipse detection;

if said object being occluded or object shape detection having to be switched to ellipse detection, performing ellipse detection on said foreground object;

determining whether said foreground object having an ellipse feature, and when said foreground object having an ellipse feature, continuing tracking said object; and

determining whether to switch from ellipse detection to object shape detection.

2. The method as claimed in claim 1, wherein said object shape detection is switched to ellipse detection if said detected object shape does not satisfy a threshold for a length to width ratio.

3. The method as claimed in claim 2, wherein said object shape detection is switched to ellipse detection when said object is leaving from the field of view.

4. The method as claimed in claim 1, wherein said foreground object is extracted through foreground and background extraction on said object.

5. The method as claimed in claim 1, wherein in the step of determining to switch from ellipse detection to object shape detection, said detection switching is based on the current frame rate of video processing.

6. The method as claimed in claim 1, wherein said foreground object is removed if said foreground object has not been detected to have an ellipse feature or the shape of said foreground object is not detected.

7. The method as claimed in claim 1, wherein when said detected object shape is not occluded, the step of determining whether to switch from object shape detection to ellipse detection further includes:

if said detected object shape greater than a threshold of the length to width ratio, switching from object shape detection to ellipse detection to continue object tracking; and

if said detected object shape not greater than a threshold of the length to width ratio, continuing object shape detection for object tracking.

8. The method as claimed in claim 1, wherein said detected object shape or ellipse feature of said foreground object is used to predict the new location of said object after moving in the next video.

9. The method as claimed in claim 1, wherein the step of determining whether said detected object shape being occluded further includes:

computing feature statistic information of said object at current time;

comparing said feature statistic information of said object at current time with feature statistic information of said same object of previous n videos to determine whether being close, if close, said object not being occluded, otherwise, comparing said feature statistic information of said object at current time with feature statistic information of neighboring object at current time to determine whether being close; and

if said feature statistic information of said object at current time being close to feature statistic information of neighboring object at current time, said object being merging with other objects;

otherwise said object being occluded by another static object.

10. The method as claimed in claim 9, wherein said feature statistic information includes the color, texture, boundary or any of the above combination of the foreground object of said object.

11. The method as claimed in claim 1, wherein the step of determining whether to switch from ellipse detection to object shape detection further includes:

determining whether current frame rate for video processing being higher than a predefined threshold;

if current frame rate for video processing being higher than said predefined threshold, setting an update threshold to a fast threshold;

otherwise, setting an update threshold to a slow threshold;

determining whether current frame rate for video processing being higher than said update threshold; and

if current frame rate for video processing being higher than said update threshold, switching from ellipse detection to object shape detection;

otherwise, continuing object tracking.

12. An apparatus for adaptive object detection, applicable to detecting an object with an ellipse feature, said apparatus comprising:

an object shape detection module for performing object shape detection on said object based on an extracted foreground from said object;

an occlusion detection module for determining whether said object being occluded according to said detected object shape;

an ellipse detection module for performing ellipse detection on said foreground object if said object being occluded or having to switch from object shape detection to ellipse detection;

an ellipse feature detection module for detecting whether said foreground object having an ellipse feature according to said ellipse detection result; and

a detection recovery module for determining whether to switch from ellipse detection to object shape detection.

13. The apparatus as claimed in claim 12, wherein said detection recovery module determines whether to switch from ellipse detection to object shape detection according to the current frame rate of video processing.

14. The apparatus as claimed in claim 12, further includes an object tracking module for continuous tracking of objects.

15. The apparatus as claimed in claim 14, wherein said object tracking includes object shape tracking and object ellipse feature information tracking.

16. The apparatus as claimed in claim 12, wherein when said object is occluded, said occlusion is either between said object and another object, or said object merging with another object.

17. The apparatus as claimed in claim 12, wherein when said object is occluded, said ellipse detection module performs ellipse detection on said foreground object.

18. The apparatus as claimed in claim 12, wherein said occlusion detection module compares current feature statistic information of said object with feature statistic information of said object in previous n videos to determine whether said object is occluded.

19. An apparatus for adaptive object detection, applicable to detecting an object with an ellipse feature, said apparatus comprising:

an object shape detection module for performing object shape detection on said object based on the extracted foreground from said object;

an occlusion detection module for determining whether said object being occluded according to said detected object shape;

an ellipse detection module for performing ellipse detection on said foreground object if said object being occluded or having to switch from object shape detection to ellipse detection;

an ellipse feature detection module for detecting whether said foreground object having an ellipse feature according to said ellipse detection result;

a detection recovery module for determining whether to switch from ellipse detection to object shape detection; and

an object tracking module for continuous tracking of objects.

20. The apparatus as claimed in claim 19, wherein said object tracking further includes object shape tracking and object ellipse feature information tracking.

21. The apparatus as claimed in claim 19, wherein said occlusion detection module compares current feature statistic information of said object with feature statistic information of said object in previous n videos to determine whether said object is occluded.

22. The apparatus as claimed in claim 19, wherein said detection recovery module determines whether to switch from ellipse detection to object shape detection according to the current frame rate of video processing.

23. The apparatus as claimed in claim 19, wherein said ellipse detection module performs ellipse detection on said foreground object when said detected object shape does not satisfy a threshold of the length to width ratio.