1. Overview Accomplishments Automatic Queen selection Side by Side Tracks
Future work

2. Accomplishments Made code more general Automatically select queens
Accounts for image size, number of people, template size, etc.
Automatically select queens
Display tracks side by side

3. Automatic Queen Selection
Algorithm
Concatenate pixels’ color values of all templates
Makes (n * n * # of people) x 3 feature matrix
n=length of square template side (e.g. 17*17)
Feature vector = [R G B]
Do kmeans clustering
Find 5 templates with largest # of pixels in small clusters
These people have unique colors and become the queens

4. Sequence 1 Queens

5. Sequence 2 Queens

6. Sequence 3 Queens

7. Sequence 4 Queens

8. Sequence 5 Queens

9. Sequence 6 Queens

10. Sequence 7 Queens

11. Side by side tracks Seq 1 Our Method X Correlation

12. Side by side tracks Seq 3 Our Method X Corelation
Seq 4 Our Method X Correlation

13. Side by side tracks Seq 5 Our Method X Correlation

14. Side by side tracks
Seq 7 Our Method X Correlation

15. Future Work Implement colored tracking Implement springs
Find more complex sequences
More sophisticated Queen selection
New name for Queens (Queen Bees)