CSE 252A: Computer Vision I

Fall 2016

Instructor: Ben Ochoa
Email: bochoa at
Office hours: M 8:00 PM-9:00 PM, EBU3B 3208

TA: Abhijit Tripathy
Email: atripath at
Office hours: Tu 5:30 PM-6:30 PM and F 4:00 PM-5:00 PM, EBU3B B250A

TA: Mihir Patankar
Email: mpatanka at
Office hours: M 10:00 AM-11:00 AM, EBU3B B250A

TA: Lenord Melvix
Email: lmelvix at
Office hours: W 10:00 AM-11:00 AM, EBU3B B250A

Note: when emailing the instructor or one of the TAs with questions about the class, please put "CSE 252A" in the subject line.

Class section ID: 882407
Lecture: MW 5:00 PM-6:20 PM, CENTR 119
Class discussion: Piazza
Grades: GradeSource

This course provides a 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.

Prerequisites: Linear algebra, calculus, probability and statistics. MATLAB or other programming experience.

Assignments will be prepared using LaTeX. Programming aspects of the assignments will be completed using MATLAB.

Late Policy: Assignments will have a hand-in procedure described with the assignment. Assignments submitted after the due date will incur a 10% per day late penalty. No assignments will be accepted after the graded assignments have been returned or the solutions have been released.

Academic Integrity Policy: Integrity of scholarship is essential for an academic community. The University expects that both faculty and students will honor this principle and in so doing protect the validity of University intellectual work. For students, this means that all academic work will be done by the individual to whom it is assigned, without unauthorized aid of any kind.

Collaboration Policy: It is expected that you complete your academic assignments on your own (or in your own group) and in your own words and code. The assignments have been developed by the instructor to facilitate your learning and to provide a method for fairly evaluating your knowledge and abilities (not the knowledge and abilities of others). So, to facilitate learning, you are authorized to discuss assignments with others; however, to ensure fair evaluations, you are not authorized to use the answers developed by another, copy the work completed by others in the past or present, or write your academic assignments in collaboration with another person. If the work you submit is determined to be other than your own, you will be reported to the Academic Integrity Office for violating UCSD's Policy on Integrity of Scholarship.



Lecture slides:

Lecture topics (tentative):

Required textbook:

Computer Vision: A Modern Approach, 2nd edition
David A. Forsyth and Jean Ponce
Pearson, 2011

Other helpful textbooks:

Computer Vision: Algorithms and Applications
Richard Szeliski
Springer, 2011
[Amazon] [Google]
Introductory Techniques for 3-D Computer Vision
Emanuele Trucco and Alessandro Verri
Prentice Hall, 1998

Multiple View Geometry in Computer Vision, 2nd edition
Richard Hartley and Andrew Zisserman
Cambridge University Press, 2004
[Cambridge Books Online] [Amazon] [Google]
(textbook for CSE 252B)

Last update: November 29, 2016