The topics studied in this course will include:
- Filtering, Image Representations, and Texture Models
- Color Vision
- Multi-view Geometry
- Projective Reconstruction
- Bayesian Vision; Statistical Classifiers
- Clustering & Segmentation; Voting Methods
- Tracking and Density Propagation
- Visual Surveillance and Activity Monitoring
- Medical Imaging
- Image Databases
- Image-Based Rendering
| Lecture | Date | Description | Readings | Assignments | Materials |
| 1 | 2/3 | Course Introduction Cameras and Lenses |
Req: FP 1.1, 2.1, 2.2, 2.3, 3.1, 3.2 |
PS0 out | Lecture 1 Lecture 1 (6 slides/page) |
| 2 | 2/5 | Image Filtering |
Req: FP 7.1 - 7.6 |
Lecture 2 Lecture 2 (6 slides/page) |
|
| 3 | 2/10 | Image Representations: pyramids | Req: FP 7.7, 9.2 |
Handout 1 Lecture 3 Lecture 3 (6 slides/page) |
|
| 4 | 2/12 | Texture | Req: FP 9.1, 9.3, 9.4 |
PS0 due |
Lecture 4 Lecture 4 (6 slides/page) |
| 2/17 | Monday Classes Held (NO LECTURE) | ||||
| 5 | 2/19 | Color | Req: FP 6.1-6.4 | PS1 out |
Lecture 5 Lecture 5 (6 slides/page) |
| 6 | 2/24 | Local Features | Req: Shi and Tomasi; Lowe | Handouts 2 - 4 Lecture 6 Lecture 6 (6 slides/page) |
|
| 7 | 2/26 | Multiview Geometry | Req: Mikolajczyk and Schmid; FP 10 | Lecture 7 Lecture 7 (6 slides/page) |
|
| 8 | 3/2 | Multiview Geometry II | Req: FP 10 | PS1 due |
Lecture 8 Lecture 8 (6 slides/page) |
| 9 | 3/4 | Affine Reconstruction | Req: FP 12.2-12.5 Opt: 12.1 |
PS2 out |
Lecture 9 Lecture 9 (6 slides/page) |
| 10 | 3/9 | Projective Geometry | Req: FP 13.0, 13.1, 13.4, 13.5 | Lecture 10 (6 slides/page) | |
| 10 | 3/10 | *** Special assignment: Horn's Seminar Wed@1 8th floor of 200 Tech Sq. *** | Horn Lecture | ||
| 11 | 3/11 | Model Based Recognition | Req: FP 18.1-18.5, Lowe | PS2 due |
Handout 4 Lecture 11 Lecture 11 (6 slides/page) |
| 12 | 3/16 | Project Reviews | EX1 out |
||
| 13 | 3/18 | No class (Horn lecture on 3/10 instead) |
EX1 due |
||
| 3/23-3/25 | Spring Break (NO LECTURE) | ||||
| 14 | 3/30 | Face Detection and Recognition I | Req: FP 22 |
Lecture 12 Lecture 12 (6 slides/page) |
|
| 15 | 4/1 | Face Detection and Recognition II | Project proposal due |
Lecture 13 | |
| 16 | 4/6 | Segmentation and Clustering |
Req: FP 14, 15.1-15.2, Comaniciu and Meer | Lecture 14 Lecture 14 (6 slides/page) Handout 5 |
|
| 17 | 4/8 | Segmentation and Fitting | Req: FP 15.3-15.5, 16 | PS3 out (4/7) |
Lecture 15 Lecture 15 (6 slides/page) |
| 18 | 4/13 | Tracking I | Req: FP 17 | Lecture 16 Lecture 16 (6 slides/page) |
|
| 19 | 4/15 | Medical Imaging | |||
| 20 | 4/20 | No class (Patriot's Day Weekend) | |||
| 21 | 4/22 | Darrell ILP Event Talk - Kresge |
PS3 due, PS4 out |
ILP Lecture ILP Lecture (6 slides/page) |
|
| 22 | 4/27 | Example-Based Methods in Computer Vision | Lecture 18 |
||
| 23 | 4/29 | Image-Based Rendering |
Req: FP 26 |
||
| 24 | 5/4 | Articulated Tracking and Shape Inference | Req: FP Extra Chapter |
PS4 due, EX2 out |
Particle Filtering |
| 25 | 5/6 | Project Presentations 11-2pm | EX2 due (5/7) |
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| 26 | 5/11 | Project week--no class |
|||
| 27 | 5/13 | Project week--no class |
Project final report due (extension to 5/17 on request) |
||
- E. H. Adelson, E. P. Simoncelli, and W. T. Freeman, Pyramids and Multiscale Representations. In Representations of Vision , pp. 3-16, 1991.
- K. Mikolajczyk and C. Schmid, A performance evaluation of local descriptors. In IEEE Conference on Computer Vision and Pattern Recognition, pp. 257-263, 2003.
- J. Shi and C. Tomasi, Good Features to Track. In IEEE Conference on Computer Vision and Pattern Recognition, 1994.
- D. G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints. In International Journal of Computer Vision , 2004.
- D. Comaniciu and P.Meer, Robust analysis of feature spaces: Color image segmentation. IEEE Conference on Computer Vision and Pattern Recognition, June 1997, 750-755.
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