Lecture Notes

LEC #	TOPICS	NOTES
1	Overview, Introduction	Course Introduction (PDF - 2.6 MB) Vision: Feature Extraction Overview (PDF - 1.9 MB) Quick MATLAB® Tutorial (PDF)
2	Vision - Image Formation and Processing
3	Vision - Feature Extraction I	(PDF - 2.4 MB)
4	PR/Vis - Feature Extraction II/Bayesian Decisions	Part 1: Bayesian Decision Theory (PDF - 1.1 MB) Part 2: Principal and Independent Component Analysis (PDF)
5	PR - Density Estimation	(PDF - 1.4 MB)
6	PR - Classification	(PDF)
7	Biological Object Recognition
8	PR - Clustering	Part 1: Techniques for Clustering (PDF) Part 2: An Application of Clustering (PDF)
9	Paper Discussion
10	App I - Object Detection/Recognition	(PDF - 1.3 MB)
11	App II - Morphable Models
12	App III - Tracking Guest Lecturer: Christopher R. Wren	(PDF - 1.0 MB) Courtesy of Christopher R. Wren. Used with permission.
13	App IV - Gesture and Action Recognition	(PDF - 3.0 MB)
14	Project Presentation