1. Week 9
Emily Hand
UNR

2. This Week Blended Template Partial SVM Model Speed Motion Model
Improvements/Debugging/Testing
Finding best parameters
Partial SVM Model
Debugging/Testing
Speed
Decrease Speed of both methods
Motion Model
Used to help detector

3. Blended Template
SVM for entire template is used to find the location in the next frame
Confidence of each block extracted using blockSVM function
A new template is constructed from positive blocks
Blended with most recent positive blocks to form a complete template

4. Blended Template Ex 1

5. Example 1 Tracked Successfully: 36 Frames
First frame – full occlusion
40%
Partial Occlusion: Frames 33-36
Full Occlusion: Frame 37
Time Per Frame: ~5 minutes
Threshold: 0.40

6. Example 1 Partial

7. Example 2

8. Example 2 Tracked Successfully: 57 frames
First full instance – end of sequence
100%
Partial Occlusion: Frames 40-48
Full Occlusion: None
Time Per Frame: ~5 minutes
Threshold: 0.40

9. Example 2 Partial

10. Example 3

11. Example 3 Tracked Successfully: 21 Frames
First full instance – full occlusion
62%
Partial Occlusion: Frames 66-69, 71-74
Full Occlusion: Frame 76
Time Per Frame: ~6 minutes
Threshold: 0.40

12. Example 3 Partial

13. Example 3 Partial

14. Example 4

15. Example 4 Tracked Successfully: 84 Frames
First full instance – end of sequence
100%
Partial Occlusion: Frames 35-42
Full Occlusion: None
Time Per Frame: ~7 minutes
Threshold: 0.40

16. Example 4

17. Example 5

18. Example 5 Tracked Successfully: 133 Frames
First full instance – end of sequence
100%
Partial Occlusion: Frames ,
Full Occlusion: None
Time Per Frame: ~30 seconds
Threshold: 0.40

19. Example 5 Partial

20. Example 5 Partial

21. Example 6

22. Example 6 Tracked Successfully: 46 Frames
First full instance – full occlusion
56%
Partial Occlusion: Frames 30-32, 42-46
Full Occlusion: 47-50
Time Per Frame: ~30 seconds
Threshold: 0.40

23. Example 6 Partial

24. Example 6 Partial

25. Example 7

26. Example 7 Tracked Successfully: 80 Frames
First full instance – end of sequence
100%
Partial Occlusion: Frames
Full Occlusion: None
Time Per Frame: ~30 seconds
Threshold: 0.40

27. Example 7 Partial

28. Conclusions
Blended Template Model works for situations without full occlusion.
In the case of full occlusion a motion model must be used
This can improve our results and allow the detector to continue locating the person after the full occlusion has passed.

29. Partial SVM Test with entire template. Find best match.
If low confidence, then find blocks with a high confidence and train new SVM with those blocks.
In next frame, test with both the entire template and the partial SVM model. Find highest match between the two.
Worse Results than we expected....

30. Partial SVM

31. Partial SVM

32. Motion Model Used to help detector. A predicted location is computed.
The confidence of each position inside of the search area is computed.
The distance of each of these points is computed from the predicted location.
If the distance is high, then the confidence at that point is decreased.

33. Blended Template Ex 1
36 Frames → 82
40% → 90%

34. Example 6
46 Frames → 82
56% → 100%

35. Speed Improvement Speed Decreased Search Area
7 minutes → seconds per frame
Much faster
If the confidence is low for several frames, then the search area grows
Once the confidence is high again, the search area shrinks around the confident area.

36. What's Next? New detection ideas 10-15 blocks in a template.
Each has its own SVM
Search for these parts and combine them to find best detection.