Method and apparatus for tracking features in a video sequence

• US 7,194,110 B2
• Filed: 12/18/2002
• Issued: 03/20/2007
• Est. Priority Date: 12/18/2002
• Status: Expired due to Fees

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Qian, Richard J.
• Primary Examiner(s): Bella; Matthew C.
• Assistant Examiner(s): SHAH, UTPAL D
• Application Number:
  US10/323,322
• Publication Number:
  US 20040120548A1
• Time in Patent Office: 1,553 Days
• Field of Search: 382/103, 382/190, 348/169
• US Class Current: 382/103
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments

Abstract

A method for performing feature tracking includes generating a pool of candidates on an image frame for a first feature point from information about a pool of candidates for a second feature point on a previous image frame.

Claims

1. A method for performing feature tracking on image frames, comprising:

initializing first and second feature points on a first image frame;

generating candidates for the first and second feature points on a second image frame; and

generating candidates for the first feature point on a third image frame from information about candidates for the second feature point on the second image frame, wherein the first, second, and third image frames generate a video sequence.

2. The method of claim 1, wherein initializing the feature points on the first image frame comprises utilizing user responses.

3. The method of claim 1, wherein initializing the feature points on the first image frame comprises performing feature point detection.

4. The method of claim 1, wherein generating the candidates comprises performing template matching.

5. The method of claim 1, wherein generating the candidates comprises performing feature point matching.

6. The method of claim 1, wherein generating candidates for the first feature point on the third image frame from the information about the candidates for the second feature point on the second image frame comprises:

selecting one of the candidates for the second feature point on the second image frame;

projecting a fixed distance between the first and second feature points from a position of the candidate selected; and

selecting a candidate in a neighborhood of the fixed distance.

7. The method of claim 1, further comprising generating candidates for the first feature point on the third image frame from information about the candidates for a third feature point on the second image frame.

8. The method of claim 1, wherein generating candidates for the first feature point on the third image frame comprises generating a series of temporary candidates based on information about previously generated candidates.

9. The method of claim 1, further comprising generating probability values for each of the candidates for the first feature point on the third image frame.

10. The method of claim 9, wherein generating probability values for each of the candidates for the first feature point on the third image frame comprises comparing each of the candidates with a selected candidate for the first feature point on the second image frame.

11. The method of claim 9, wherein generating probability values for each of the candidates for the first feature point on the third image frame comprises comparing each of the candidates with an average of the candidates for the first feature point on the second image frame.

12. The method of claim 9, wherein generating probability values for each of the candidates for the first feature point on the third image frame comprises comparing each of the candidates with an average of selected candidate for the first feature point for previous image frames.

13. The method of claim 1, further comprising selecting a candidate for each of the feature points on the second image frame.

14. The method of claim 1, further comprising selecting a candidate for the first feature point on the third image frame.

15. A machine-readable medium having stored thereon sequences of instructions, the sequences of instructions including instructions which, when executed by a processor, causes the processor to perform:

initializing first and second feature points on a first image frame;

generating candidates for the first and second feature points on a second image frame; and

generating candidates for the first feature point on a third image frame from information about candidates for the second feature point on the second image frame, wherein the first, second, and third image frames generate a video sequence.

16. The machine-readable medium of claim 15, wherein generating candidates for the first feature point on the third image frame from the information about the candidate for the second feature point on the second image frame comprises:

selecting one of the candidates for the second feature point on the second image frame;

projecting a fixed distance between the first and second feature points from a position of the candidate selected; and

selecting a candidate in a neighborhood of the fixed distance.

17. The machine-readable medium of claim 15, further comprising instructions which, when executed by the processor, causes the processor to perform generating candidates for the first feature point on the third image from information about the candidate for a third feature point on the second image frame.

18. The machine-readable medium of claim 15, wherein generating candidates for the first feature point on the third image frame comprises generating a series of temporary candidates based on information about previously generated candidates.

19. The machine-readable medium of claim 15, further comprising instructions which, when executed by the processor, causes the processor to perform generating probability values for each of the candidates for the first feature point on the third image frame.

20. An image processing unit, comprising:

a feature initialization unit to initialize first and second feature points on a first image frame;

a tracking unit to generate candidates for the first and second feature points on a second image frame and to generate candidates for the first feature point on a third image frame from information about candidates for the second feature point on the second image frame, wherein the first, second, and third image frames generate a video sequence.

21. The apparatus of claim 20, wherein the feature utilization unit initializes the feature points on the first image frame by utilizing user responses.

22. The apparatus of claim 20, wherein the feature utilization unit initializes the feature points on the first image frame by performing feature point detection.

23. The apparatus of claim 20, wherein the tracking unit comprises an initial candidate pool selection unit to generate the candidates by performing template matching.

24. The apparatus of claim 20, wherein the tracking unit comprises a feature point matching unit to generate the candidates by performing feature point matching.

25. The apparatus of claim 20, wherein the tracking unit comprises:

a candidate pool evolution unit to select one of the candidates for the second feature point on the second image frame and to project a fixed distance between the first and second feature points from a position of the candidate selected; and

a feature point matching unit to select a candidate in a neighborhood of the fixed distance.

26. The apparatus of claim 20, wherein the tracking unit comprises a candidate pool evolution unit to generate candidates for the first feature point on the third image frame from information about the candidates for a third feature point on the second image frame.

27. The apparatus of claim 20, wherein the tracking unit comprises a candidate pool evolution unit to generate candidates for the first feature point on the third image frame by generating a series of temporary candidates based on information about previously generated candidates.

28. The apparatus of claim 20, wherein the tracking unit comprises a feature point matching unit to generate probability values for each of the candidates for the first feature point on the third image frame.

29. The apparatus of claim 28, wherein generating probability values for each of the candidates for the first feature point on the third image frame comprises comparing each of the candidates with a selected candidate for the first feature point on the second image frame.

30. The apparatus of claim 28, wherein generating probability values for each of the candidates for the first feature point on the third image frame comprises comparing each of the candidates with an average of the candidates for the first feature point on the second image frame.

31. The apparatus of claim 28, wherein generating probability values for each of the candidates for the first feature point on the third image frame comprises comparing each of the candidates with an average of selected candidate for the first feature point for previous image frames.

32. The apparatus of claim 20, wherein the tracking unit comprises a feature point matching unit to select a candidate for each of the feature points on the second image frame.

33. The apparatus of claim 20, wherein the tracking unit comprises a feature point matching unit to select a candidate for the first feature point on the third image frame.