198:534   Computer Vision

Spring 2015

 

 

Class Materials Page

 

 

Lectures:

 

Date

 

Lecture

Extras

1/26/15

Week 1

1- Introduction to Computer Vision and Applications

 

 

2/2/15

 

Class was cancelled due to school closure

 

2/9/15

Week 2

2- Human Vision

3- Cameras and Lenses 

 

Recommended Reading:

“Early Vision” Chapter 1 of  Martha J. Farah “The Cognitive Neuroscience of Vision” Blackwell 2000

 

 David H. Hubel & Torsten N. Wiesel “Brain Mechanisms of Vision” Scientific American, 1979.

 

2/16/15

Week 3

4- Binary Image Analysis

 

 

2/23/15

Week 4

6- Linear Filters  

7- Edge Detection

 

 

3/2/15

Week 5

8- Fourier Transform of images

9 - Texture

 

 

3/9/15

Week 6

10.1 - Local Features

10.2 -  Color

 

3/23/15

Week 7

11- Camera Geometry 

 

Introduction to Projective Geometry

3/30/15

Week 8

12 - Camera Calibration

Zhengyou Zhang Chapter on Camera Calibration.

4/6/15

Week 9

13- Perceptual Grouping and Segmentation by Clustering

 

 

Jianbo Shi and Jitendra Malik “Normalized Cuts and Image Segmentation”

4/13/15

Week 10

 

14 -  Segmentation- statistical methods, mean shift

 

15 – Segmentation: Model Fitting  

 

 

 

D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis,"

4/20/15

Week 11

 

16- - Stereo imaging

 

 

4/27/15

Week 12

17- Multiple View Geometry and Structure from Motion

 

Midterm

 

 

5/4/15

Week 13

 

18 - 3D Model-based Recognition and Pose Recovery 

 

 

 

Recommended Reading: Wolfson, H.J. & Rigoutsos, I (1997). “Geometric Hashing: An Overview.” IEEE Computational Science and Engineering, 4(4), 10-21

5/11/15

Week 14

 

19 - Appearance-based Vision

 

20- Local-Feature based Object Detection and Recognition

 

DiCarlo et al 2012 “How Does the Brain Solve Visual Object Recognition?”, Neuron 73, February 9, 2012

 

 

 

 

 

 

Sample Midterm Exam Question

 

Reading materials:

 

 

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