1. Incremental learning for Robust Visual Tracking 2013-10-08 Ko Dae-Won

2.  PCA  Face recognition for PCA  Sequencial Inference Model  Dynamical model  Observation model 6. Summary of the tracking algorithm Contents Incremental learning for Robust Visual Tracking

3. 1. PCA(Principal Component Analysis) Incremental learning for Robust Visual Tracking

4. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

5. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

6. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

7. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

8. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

9. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

10. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

11. 2. Face recognition for PCA Incremental learning for Robust Visual Tracking

12. Visual tracking problem : an inference task in a Markov model with hidden state variables 3. Sequencial Inference Model Incremental learning for Robust Visual Tracking

13. 3. Sequencial Inference Model Incremental learning for Robust Visual Tracking

14. 3. Sequencial Inference Model Incremental learning for Robust Visual Tracking

15. 4. Dynamical Model Incremental learning for Robust Visual Tracking

16. 4. Dynamical Model Incremental learning for Robust Visual Tracking

17. 5. Observation Model Incremental learning for Robust Visual Tracking

18. 5. Observation Model Incremental learning for Robust Visual Tracking

19. 5. Observation Model Incremental learning for Robust Visual Tracking

20. 6. Summary of the tracking algorithm 20 Incremental learning for Robust Visual Tracking

21. 6. Summary of the tracking algorithm Incremental learning for Robust Visual Tracking 21

22. 5. Store the image window. When the desired number of new images have been accumulated, perform an incremental update of eigenbasis, mean and effective number of observations. 6. Go to step 3. 6. Summary of the tracking algorithm 22 Incremental learning for Robust Visual Tracking

23. 5. Store the image window. When the desired number of new images have been accumulated, perform an incremental update of eigenbasis, mean and effective number of observations. 6. Go to step 3. 6. Summary of the tracking algorithm 23 Incremental learning for Robust Visual Tracking