CSE252A
Computer Vision I

Tuesday, Thursday 5:00-6:20 pm
Center Hall, Room 217A

Class Mailing List: UCSD Listserve cse252a-l
Class Web Board: QuickTopic

Class web page: http://cseweb.ucsd.edu/classes/fa09/cse252a

News:

9/24: There will be no classes next week. The lectures will be made up in the following weeks. Time and location to be announced.

10/9: HW1 assigned. Due 10/20

10/22: HW2 assigned. Due 11/3

11/3: HW2 Due Date Extended. Due 11/10

11/6/09: HW3 assigned. Due 11/24

11/25/09: HW4 assigned. Due 12/4

12/3/09:Final exam, Friday 12/11/09 7:00PM-10:00PM Center Hall 217A, Sample final exam

Course Information:

Instructor: David Kriegman
Office: EBU3B, Room 4120
Phone: (858) 822-2424
Email: kriegman at cs.ucsd.edu
Office Hours: Th 2:00 – 3:30pm

TA: Steve Branson

Email: sbranson at cs.ucsd.edu

Office: EBU3B, Room B240A (basement)

Office Hours: Monday 2:00-3:00

Class Description:
Comprehensive introduction to computer vision providing broad coverage including low level vision (image formation, photometry, color, image feature detection), inferring 3D properties from images (shape-from-shading, stereo vision, motion interpretation) and object recognition. A companion course, CSE252B, Computer Vision II is taught in the spring quarter. 4 units.

Required Text:
"Computer vision: A Modern Approach," David A. Forsyth, Jean Ponce, Prentice Hall, ISBN: 0130851981

Supplemental Text:

“Computer Vision: Algorithms and Applications”, Richard Szeliski, A draft of the book, which is currently being written, is available at: http://research.microsoft.com/en-us/um/people/szeliski/Book/.

Prerequisites:
Linear algebra and Multivariable calculus (e.g., Math 20A & 20F), programming, data structure/algorithms (e.g., CSE100). Probability can also be useful.

Programming:
Assignments will include both written problem sets and programming assignments in Matlab. Students can either purchase the Matlab student edition or use copies available on University machines such as are available in the APE Lab.

Grading:
Assignments: 60%
Final Exam: 40%

Late Policy:
Written homework will be due in class and accepted thereafter with a penalty of 10% per day starting from the due date. Programming assignments will have a hand-in procedure described with the assignment, and also has a 10% per day late penalty. No assignments will be accepted after the graded assignments have been returned or the solutions have been released.

Assignments

Homework 0 [Due 10/13]: Getting Started with Matlab

Homework 1 [Due 10/20]: Camera & Lenses, Rigid Transformations, and Radiometry

· For those who don't have a copy of the book, use this copy Homework 1 modified

· house_model.m

Homework 2 [Due 11/10]: Photometric Stereo and Specularity Removal

Homework 3 [Due 11/24]: Dense Stereo Matching

Images used for this assignment: hw3_images.zip

Homework 4 [Due 12/4]: Optical Flow

Images used for this assignment: hw4_images.zip

Syllabus:

[ Note that this Syllabus is tentative & subject to change ]

Week	Date / Link to lecture notes	Topic / Readings
1	Sep. 24 Linear algebra review Random variables review	Intro to Computer Vision
2	Sep. 29 Oct. 1	There will be no lectures this week, and we will make them up in subsequent weeks
3	Oct. 6	Rigid Transformatoins SE(3), SO(3), Camera & Lenses, F&P Sec. 2.1, F&P Chap. 1
	Oct. 8	Perspective, Affine, orthographic projection, F&P 2.2, 2.3
	Extra Lecture	Human Visual System
4	Oct. 13	Radiometry (Irradiance, Radiance, BRDF), F&P Chapter 4; Supplemental reading Glassner Chapter 13 (requires campus network connection)
	Oct. 15	Special BRDF's, Light Sources, Photometric Stereo, F&P, 5.2-5.4; Supplemental reading Glassner pp 726-752
	Extra Lecture	Photometric stereo
5	Oct. 20 Irradiance example problem	Illumination Cones, Belhumeur, Kriegman, What Is the Set of Images of an Object under All Possible Illumination Conditions?, IJCV 28(3), 1998, 245-260
	Oct. 22 white background version)	Color; F&P, Chap. 6 Some on-line sources include: Basics of Color, A FAQ on Color
6	Oct. 27	Color, Dichromatic model
	Oct. 29	Filtering F&P Chap. 7, 8
6	Nov. 3	Edges
	Nov. 5	Epipolar Constraint and Stereo I, F&P Sec. 10.1Stereo II, Dynamic Programming, Chapter 11
7	Nov. 10	Optical Flow, Trucco and Verri, pp. 178-194
	Nov. 12	Infinitesimal structure from Motion, Trucco and Verri pp. 195-202, and pgs. 208-211
8	Nov. 17	Tracking, F&P Chap.17
	Nov. 19	Statistical Pattern Recognition, F&P 22.1-22.3
9	Nov. 24	Support Vector Machines & Kernel Methods, F&P Sec. 22.5, 22.8
10	Dec. 1	Appearance-based Recognition, Eigenface, Fisherface, Appearance Manifolds
	Dec. 3	Model-based recognition, F&P Chap. 18

Notes and Links:

Programming languages:
The primary language will be Matlab. . Click here for Serge Belongie's Matlab resource links.

Other excellent textbooks:
Introductory Techniques for 3-D Computer Vision, Trucco and Verri (textbook for CSE152)
An Invitation to 3D Vision: From Images to Geometric Models, Ma, Soatto, Kosecka and Sastry, Springer Verlag, 2003, ISBN 0-387-00893-4 (textbook for CSE252B)

Some useful links:
Camera Calibration Toolbox for Matlab (Bouguet)
Microsoft Camera Calibration Code (Zhang)
Intel OpenCV
CVonline
The Computer Vision Home Page
Handy Math reference: MathWorld

CSE252A Computer Vision I

Tuesday, Thursday 5:00-6:20 pm Center Hall, Room 217A