198:534 Computer Vision

Spring 2011

Class Materials Page

• Lectures
• Readings
• Homework Assignments
• Resources

Lectures:

Date		Lecture	Extras
1/18/11	Week 1	1- Introduction to Computer Vision and Applications
1/25/11	Week 2	2- Human Vision 3- Cameras and Lenses	Recommended Reading: David H. Hubel & Torsten N. Wiesel “Brain Mechanisms of Vision” Scientific American, 1979.
2/1/11	Week 3	4- Binary Image Analysis
2/8/11	Week 4	6- Linear Filters 7- Edge Detection
2/15/11	Week 5	8- Fourier Transform of images - Texture
2/22/11	Week 6	9- Camera Geometry
3/1/11	Week 7	10 - Camera Calibration
3/8/11	Week 8	10 - Camera Calibration (Cont.) 11 - Stereo imaging
3/22/11	Week 9	12 - Multiple View Geometry
3/29/11	Week 10	13- Multiple View Geometry (Cont)
4/5/11	Week 11	14- Perceptual Grouping and Segmentation by Clustering - Segmentation- statistical methods, mean shift	Jianbo Shi and Jitendra Malik “Normalized Cuts and Image Segmentation” D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis,"
4/12/11	Week 12	Midterm 15 - Model Fitting 16 - 3D Model-based Recognition and Pose Recovery - RANSAC	Recommended Reading: Wolfson, H.J. & Rigoutsos, I (1997). “Geometric Hashing: An Overview.” IEEE Computational Science and Engineering, 4(4), 10-21
4/19/11	Week 13	17- MRFs 18 - Appearance-based Vision
4/26/11	Week 14	19- Object Detection and Recognition

Sample Midterm Exam Question

Reading materials:

• David H. Hubel & Torsten N. Wiesel “Brain Mechanisms of Vision” Scientific American, 1979.
• [required reading] Serge Belongie, Jitendra Malik and Jan Puzicha “Shape Matching and Object Recognition Using Shape Contexts” (PAMI April 2002)
• [required reading] Jianbo Shi and Jitendra Malik “Normalized Cuts and Image Segmentation” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 22 No. 0, August 2000
• D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 603--619, 2002.
• Yuri Boykov, Olga Veksler, Ramin Zabih "Fast Approximate Energy Minimization via Graph Cuts". In IEEE transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 23, no. 11, pp. 1222-1239, 2001.

Homework Assignments:

Assignments will be on Sakai.

General Useful Computer Vision Resources:

§ Computer Vision Home Page (CMU): http://www-cgi.cs.cmu.edu/afs/cs/project/cil/ftp/html/vision.html

§ CV online: http://www.dai.ed.ac.uk/CVonline/

§ Keith Price Annotated Computer Vision Bibliography at USC:

http://iris.usc.edu/Vision-Notes/bibliography/contents.html

§ Open CV: Intel Open Source CV library.

http://www.intel.com/research/mrl/research/opencv/

§ Microsoft Vision SDK http://research.microsoft.com/projects/VisSDK/

§ Matlab Image Processing toolbox:

http://www.mathworks.com/access/helpdesk/help/toolbox/images/images.shtml

Matlab Resources

q The most popular Matlab tutorial is the one written by Kermit Sigmon of University of Florida:

Matlab Tutorial by Prof Sigmon

q An extensive tutorial from Mathworks

q Online resources for Matlab Tutorial are:

1. http://math.ucsd.edu/~driver/21d-s99/matlab-primer.html

2. http://www4.ncsu.edu/unity/users/p/pfackler/www/MPRIMER.htm

3. http://www.glue.umd.edu/~nsw/ench250/primer.htm

4. http://www.math.ukans.edu/docs/matlab/matlab-primer.html

5. http://www.math.ufl.edu/help/matlab-tutorial/

6. http://www-personal.engin.umich.edu/~tilbury/tutorials/matlab_tutorial.html

q Some resources for image processing using Matlab follows:

1. http://www.cnb.uam.es/~coss/ImageProcessing/Tutorial/

2. http://www.csee.wvu.edu/~trapp/wvumatlab.htm

3. http://www.mathworks.com/products/image/description1.jsp

4. http://amath.colorado.edu/courses/4720/2000Spr/Labs/Worksheets/Matlab_tutorial/matlabimpr.html