1. Interactive Offline Tracking for Color Objects
ICCV 2007
Yichen Wei , Jian Sun, Xiaoou Tang, Heung-Yeung Shum
Microsoft Research Asia
Yuan-Hao Lai

2. [Interactive Offline Tracking for Color Objects]
Interactive offline for generic objects
User refine tracking result
train a object detector from user input
use temporal coherence to generate trajectories
optimal path found by dynamic programming

3. [Trial-and-error way]
Tracks the object from the first frame
User goes back several frames to correct
May fail frequently due to continuous changes
No guarantee to connect the tracks between two neighboring keyframes consistently and smoothly

4. works like an optimized “interpolation”
[Offline tracking]
global optimization problem to find an optimal path in the entire video
works like an optimized “interpolation”
refine at any frame, restart the optimization
fps on a 320×240 video

5. [Minimize global cost] xi: object at i L: user input d(·):data term s(·): smoothness term

6. [Offline tracking]
User starts the tracking by specifying first and last keyframe, system minimizes (1)
User then adds or modifies keyframes to correct
Exhaustive search: O(WH(wh+B)) →20 seconds
Proposed method
Detector to quickly reject 98% of non-object regions
Trajectory growing algorithm

7. [Color bin as feature]
Spatial configuration of object could easily fail
Interactive system should use flexible feature

8. [Boosted color bins]
Adaboosting

11. [Training]
Perturb the position of specified rectangle
Scale the object colors
Generate about 1000 positive and 3000 negative samples per keyframe for training
Using at most 10 color bins are good enough to achieve reasonable training errors

14. [Experimental Results]

15. Fast but memory consuming
[Pre-computation ]
Fast but memory consuming
for a 320 × 240 frame, storing all 13 histograms with 8 bins costs about 30MB
only integral histograms for several keyframes are loaded
Memory cost is 0.7MB/I-frame per frame

16. [Timing]

17. [Detection evaluation]

19. [Conclusion / Future work]
Interactive offline tracking for color objects
via an efficient global optimization framework
Obtain high quality results for difficult videos in a short time
Combining other features?
Interactive multiple object tracking?

20. Thank You.