Course calendar (tentative--subject to change)

The course calendar below gives the lecture topics, assignment and due dates for projects.  The calendar is subject to change during the quarter, and we will remind you as each of the due dates comes near.

Week

Topics

Readings

Assignments

1

March 31 (Steve)

Intro        [ppt, pdf, html]
Filtering  [ppt, pdf, html
 

• Szeliski, Ch 1.0, 3.1-3.2
• (optional) bilateral filtering

 

 

April 2 (Steve)

Image features   [ppt, pdf, html]

• Szeliski, Ch.4.1
• (optional) multi-image matching [Brown05]
• (optional) SIFT [Lowe04]
• (optional) affine covariant features

Project 1 assigned

 

2

7 (Steve)

Features (continued)
Edges and Scale  [ppt, pdf, html]

• Cipolla & Gee on edge detection

• Szeliski, Ch 4.1.2, 4.1.3
 

 

9 (Steve)

Cameras, projection  [ppt, pdf, html]

• Szeliski, Ch 3.4-3.5, 2.1
• (optional) Nalwa 2.1

 

3

14 (Rick)

Image stitching: motion models,
 warping, RANSAC  [ppt, pdf]

• Szeliski, Ch 5.1, 8.1
• (optional) Brown & Lowe, Recognising Panoramas

• (optional)  Szeliski & Shum, SIGGRAPH 97

• (optional) RANSAC

 

16 (Rick)

Image stitching: blending, deghosting 

• Szeliski, Ch 8.2-8.3
 

Project 1 due

Project 2 assigned

 

4

21 (Rick)

Computational Photography: HDR blending and tone mapping, flash-no-flash, Photomontage, Poisson blending
[ppt, pdf]

Texture quilting [ppt, pdf]

• Debevec and Malik, Recovering High Dynamic Range Radiance Maps from Photographs. In SIGGRAPH 97, August 1997.

• S. B. Kang et al. High dynamic range video. SIGGRAPH 2003.

• D. Lischinski. Interactive local adjustment of tonal values. SIGGRAPH 2006.

• G. Petschnigg et al. Digital photography with flash and no-flash image pairs. SIGGRAPH 2004.

• P. Pιrez et al. Poisson image editing. SIGGRAPH 2003.

 

23 (Rick)

Optical flow [ppt, pdf]

• Szeliski, Ch. 7.1-7.2 (skip 7.1.2), 7.4
• (optional) Bergen et al. Hierarchical model-based motion estimation. ECCV’92, pp. 237–252

 

5

28 (Rick)

Recognition 1: general concepts and eigenfaces [ppt, pdf]

 

• C. Bishop, “Neural Networks for Pattern Recognition”, Oxford University Press, 1998, Chapter 1.
• (optional) Forsyth and Ponce, 22.3 (eigenfaces)

• Viola, P. A. and Jones, M. J. (2004). Robust real-time face detection. IJCV, 57(2), 137–154

 

30 (Rick)

Recognition 2: feature-based instance and category recognition [ppt, pdf]

CVPR'2007 Tutorial on Recognizing and Learning Object Categories (abridged)
[ppt, pdf]
 

• Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition Fergus, R. , Perona, P. and Zisserman, A. International Journal of Computer Vision, Vol. 71(3), 273-303, March 2007

Project 2 due

Project 3 assigned

 

6

May 5 (Rick)

Projective geometry  [ppt, pdf]
Single view modeling [Criminisi]
 

.• Mundy, J.L. and Zisserman, A., Geometric Invariance in Computer Vision, Appendix: Projective Geometry for Machine Vision, MIT Press, Cambridge, MA, 1992, (read  23.1 - 23.5, 23.10)

 Project 4 assigned

7 (Rick)

Structure from motion [ppt, pdf]
Photo Tourism [ppt, pdf]
3D modeling: Facade, Sudipta's work

• epipolar geometry, essential matrix, etc:  online tutorial
• see Marc Pollefeys nice online notes on bundle adjustment
• N. Snavely, S. M. Seitz, and R. Szeliski. Photo tourism: Exploring photo collections in 3D. SIGGRAPH 2006.

 

7

12 (Rick)

Stereo [ppt, pdf]

• D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV, 47(1):7-42, 2002.

Project 3 due

 

 

 

14 (Steve)

Multi-view stereo  [ppt, pdf]
 

• S. Seitz et al. A comparison and evaluation of multi-view stereo reconstruction algorithms. CVPR'2006

Project 4 proposal due by noon (e-mail instructors)
 

8

19 (Steve)

Light, color   [ppt, pdf, html]
photometric stereo 
 [ppt, pdf, html]
 

• Szeliski, Ch. 2.3.2
 

 

21

Class project proposals
 

• (optional) Forsyth & Ponce, Chapter 7
• see slides for (optional) supplementary refs

 

Project 4 status report due (in class)

9

26 no class

(Memorial Day, no class)
 



 

 

28 (Guest lecture: Ian Simon)

Segmentation:
manual and interactive   [ppt, pdf, html]
 

 

 

10

June 2 (Steve)

Matting and Transparency   [ppt, pdf, html]

• Y. Chuang et al. A Bayesian Approach to Digital Matting, CVPR 2001.
• (optional) D. E. Zongker et al. Environment matting and compositing, SIGGRAPH 1999.

• (optional) S. Nayar et al. Fast Separation of Direct and Global Images, SIGGRAPH 2006.

 

4 Final project presentations

Project 4 final presentation (in class)

6 Final project writeups  

Project 4 final writeup