•  [12.01.11] We have released detailed instructions on project presentation (see Project Submission Details and Project Presentation Guidelines sections on Course project page).

•  [11.09.11] Problem Set 4 extra office hour is coming up on 11/29 (Tuesday) 7pm-9pm in Gates 104.

•  [11.09.11] Problem Set 3 extra office hour is coming up following Saturday 3pm-6 in Gates 104.

•  [11.02.11] Problem Set 3 is now available on the website!

•  [10.30.11] The course project milestone deadline is postponed to Nov 18.

•  [10.22.11] Problem Set 2 extra office hours is coming up the following Thursday 8pm-10pm in Gates 104.

•  [10.07.11] Problem Set 1 extra office hours is coming up the following Thursday 7pm-9pm in Gates 104.

•  [10.03.11] Register for 1 unit CS 231AL course if you would like to take the course for 4 units.

•  [09.29.11] Problem Set 0 section is this Saturday 3pm-5 in Gates 104.

•  [09.28.11] Please read an email regrading taking the course in 3 or 4 units and respond ASAP!

•  [09.26.11] Weekly TA section is at Friday 2:15pm-3:05 in Gates B01.

•  [09.26.11] Problem Set 0 is linked in the syllabus and lecture notes page.

•  [09.26.11] Welcome to CS231A, formerly known as CS223B.


Instructor: Prof. Fei-Fei Li

Office: Room 246, Gates Building

Phone: (650) 725-3860

Office hours: M 11am-12


Course Team Email:
Important: Please use the Piazza for all questions related to lectures, problem sets or projects. *ONLY* email the Course Team Email when absolutely necessary such as for personal questions. Class/homework/project questions will be answered FASTER if asked on the Piazza.


Not registered through Axess? Sign up to the guest course mailing list to receive latest updates about CS231A: cs231a-aut1112-guests


Course Assistants:

Kevin Tang

Office hours: Th 4pm-5

Location: B24A, Gates Building


Yongwhan Lim

Office hours: F 3:30pm-4:30

Location: B24A, Gates Building


Jiahui Shi

Office hours: M 4pm-5

Location: B24A, Gates Building


Hao Su

Office hours: T 5:45pm-6:45

Location: B24A, Gates Building



Class Time and Location:

Lectures: MW 9:30am-10:45 (Gates B01)

TA Sections: F 2:15pm-3:05 (Gates B01)


Course Description:

An introduction to the concepts and applications in computer vision. Topics include: cameras and projection models, low-level image processing methods such as filtering and edge detection; mid-level vision topics such as segmentation and clustering; shape reconstruction from stereo, as well as high-level vision tasks such as object recognition, scene recognition, face detection and human motion categorization.


Grading Policy:

Problem Sets: 40%
 •  PS0: 4%
 •  PS1: 9%
 •  PS2: 9%
 •  PS3: 9%
 •  PS4: 9%

Midterm exam: 20%

Final project: 40% (please click here for detailed instructions)

Late policy:
 • 5 free late days for PS only (not course project)– use them in your ways;
 • After you have finished using all of your late days, there is a 25% off per day late penalty;
 • No submission is accepted after 3 late days per PS.

Assignment Submission:

All assignments are due by the beginning of class. Please submit your assignments as hardcopy. If you cannot submit in class, write down the date and time of submission as well as the late days used for that problem set, and leave it in the CS231A submission cabinet near the east entrance of Gates building. It is an honor code violation to write down the wrong time.

SCPD Students: Please email your solutions to and cc to Write "Problem Set PID Submission" on the Subject of the email, where PID is the problem set number (1/2/3/4). Each homework should be emailed as a SINGLE pdf file. Additionally, all SCPD students should also include the Homework Routing Form available here. This should appear as the very first page of your Homework solutions.

Late policy: Each student will have a total of five free late (calendar) days to use for the assignments. Once these late days are exhausted, any assignments turned in late will be penalized 25% per late day. However, no assignment will be accepted more than three days after its due date. Each 24 hours or part thereof that an assignment is late uses up one full late day. Late days cannot be used for the final project.


Computer Vision is a field that spans multiple disciplines and draws links to several traditional fields such as image processing, optics, probability and statistics, etc. Students who have done well in previous years in general have good and solid knowledge in linear algebra, probability, statistics and machine learning, as well as decent programming skills. Though not an absolute requirement, it is encouraged and preferred that you have at least taken either CS221 or CS229, or have equivalent knowledge.



No required textbooks; Suggested textbooks:
Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010.
Learning OpenCV, by Gary Bradski & Adrian Kaehler, O'Reilly Media, 2008.
Multiple View Geometry in Computer Vision, 2nd Edition, by R. Hartley, and A. Zisserman, Cambridge University Press, 2004.
Computer Vision: A Modern Approach, by D.A. Forsyth and J. Ponce, Prentice Hall, 2002.
Pattern Classification (2nd Edition), by R.O. Duda, P.E. Hart, and D.G. Stork, Wiley-Interscience, 2000.