| Date | Topic | Reference | HW Due |
| WEEK 1: Intro | |||
| 9/24 | Introduction | Ballard & Brown Chap 1 | |
| WEEK 2: Linear filtering | |||
| 9/29 | Filtering 1 | Forsyth & Ponce Chap 7 | |
| 10/1 | Filtering 2 | Forsyth & Ponce Chap 7 | |
| WEEK 3: Basic image processing | |||
| 10/6 | Template matching (bayesian models, invariance, ROC, NMS) | Probability chapter from Forsyth & Ponce | HW1 |
| 10/8 | Binary images (edges,morphology,medial axis) | Forsyth and Ponce Chap 8 | |
| WEEK 4: Fitting | |||
| 10/13 | Line fitting, hough transforms | Forsyth & Ponce Chap 15 | |
| 10/15 | Ransac | Forsyth & Ponce Chap 15 | |
| WEEK 5: Texture | |||
| 10/20 | Texture | Forsyth & Ponce Chap 9 | HW2 |
| 10/22 | Synthesis | Texture synthesis | |
| WEEK 6: Segmentation | |||
| 10/27 | Clustering, MRFs | Meanshift, Graphcuts | |
| 10/29 | Level sets & top-down segmentation | CVPR tutorial | |
| WEEK 7: Intro to recognition | |||
| 11/3 | Digit recognition | Convolutional neural nets,Tangent distance, Decision trees | |
| 11/5 | Pattern classification (SVMs, boosting) | HOG templates, Face detection | |
| WEEK 8: Modeling appearance variation | |||
| 11/10 | Deformable matching | Active appearance models | |
| 11/12 | Manifolds (eigenfaces) | Eigenfaces, Eigenobjects | proposal, HW3 |
| WEEK 9: Modeling geometric variation | |||
| 11/17 | Pictorial structures | Pictorial structures | |
| 11/19 | Discriminative part models | Latent models | |
| WEEK 10: Video processing | |||
| 11/24 | Video and optical flow | Horn and Schunk | |
| 11/26 | Tracking | Forysth and Ponce, Chap 17 | |
| WEEK 11: Looking forward (3D and functional objects) | |||
| 12/1 | Three-dimensional representations | Forsyth and Ponce, Chap 20 | |
| 12/3 | Affordances, Taxonomies, Partonomies | Gibson's manuscript | |
| WEEK 12: Final projects | |||
| 12/10 | Presentations | Instructions | |