1. Tracking Learning Detection
A Camera that Learns.

2. Why is object tracking so important ?
vehicle detection
motion capture
robot vision
Why is object tracking so important ?
scene analysis
hand recognition
surveillance

4. What is TLD intuitively?
Outline
Why TLD?
- Traditional methods - Challenges to old ways
What is TLD intuitively?
- Framework - Key ideas
How does TLD work exactly?
- Tracking - Learning - Detection - TLD
Experiment Results

5. Why TLD ?

6. Why TLD ?
你會怎麼做?

7. Why TLD ? - Traditional method 1 :
Tracking
Estimate motion over frames
Only need initialization.
Appearance changing & Partial occlusions. (?)
Accumulate error.
Fail if the object disappears.

8. Why TLD ? - Traditional method 2 :
Detection
Off-line
Learning
Scan every frame independently
Do not fail if the object disappears.
Need off-line training.
Appearance changing & Partial occlusions.

9. Why TLD ? - Challenges to old ways
Not fail if the object disappears.
Appearance changing.
Partial occlusions.

10. Why TLD ? - Challenges to old ways
Not fail if the object disappears.
TLD
is an algorithm
that can solve all these tasks !
Appearance changing.
Partial occlusions.

11. What is TLD intuitively?

12. What is TLD intuitively? - Framework
Tracking
Off-line
Learning
Detection

13. What is TLD intuitively? - Framework
On-line
Learning
Trajectory
fragment
Location
Update
Tracking
Detection
Update

14. What is TLD intuitively? - Key ideas 1 : Learning
Updates
training examples
(add/delete)
Detect
Track & detect
Update detector
Appearance changing.
Track

15. What is TLD intuitively? - Key ideas 2 : Updating
True trajectory
Tracking
Detection
TLD
Not fail if no object.
Partial occlusions.

16. How does TLD work exactly?

17. How does TLD work exactly? - Framework

18. How does TLD work exactly? - Tracking
1.Reliable point selection:
- Forward-backward selection
Choose point 1
Discard point 2
- Use forward-backward selection to select 50% of the most reliable points.

19. How does TLD work exactly? - Tracking
2.Median-Flow tracker:
and estimates displacement
using median with
confidence proportional
to (1/scale of the median).
Tracks the reliable points
between consecutive frames ,

20. How does TLD work exactly? - Framework

21. How does TLD work exactly? - Detection
2bitBP features
Scanning
window
2BitBP : invariance to illumination
RF : fast
Illumination
invariance
2bitBP
features

22. How does TLD work exactly? - Detection
Random Forest
Random
Forest
Posteriors
Scanning
window
2BitBP : invariance to illumination
RF : fast
If the average posteriors is larger than 50%,
consider it an object
2bitBP
features

23. How does TLD work exactly? - Detection
1-NN classifier
Confidence =d-/(d-+d+)
Feature space
Random
Forest
Posteriors
Scanning
window
2bitBP
features

24. How does TLD work exactly? - Framework
Pick the one with higher confidence score

25. How does TLD work exactly? - Learning
Feature space

26. How does TLD work exactly? - Learning
Updates
training examples
(add/delete)
Detect
Track & detect
Update detector
Track

27. How does TLD work exactly? - Learning :
Appearance changing
problem solved! 1 6 10 9

28. How does TLD work exactly? - Recap : t=0

29. How does TLD work exactly? - Recap : t=1
Decide by
confidence
score

30. How does TLD work exactly? - Recap : t=1

31. How does TLD work exactly? - Recap : t=2
Remove if
false detect

32. Experiment Result

33. Experiment Result
More vid

34. Experiment Result

35. Experiment Result

36. Thank you