Introduction to Computer Vision

Tuesday, Thursday 3:30-4:50

Warren Lecture Halls, Rm. 2205


Discuss CS 190-B Discussion

Class Mailing list: cse190-b@cs.ucsd.edu

Announcement: Final Exam, Thursday, June 12, 3:00-6:00, WLH 2205.

Instructor: David Kriegman

Office: AP&M 3101

Phone: (858) 822-2424

Email: kriegman@cs.ucsd.edu

Office Hours:    Wednesday1:00-2:30

TA: Diem Vu

Location: AP&M 3349D

Email: d1vu@cs.ucsd.edu

Office Hours: Tuesday11:00-12:30, Thursday 10:00-11:00


Class Description: The goal of computer vision is to compute properties of the three-dimensional world from images and video.Problems in this field include identifying the 3D shape of a scene, determining how things are moving, and recognizing familiar people and objects.This course provides an introduction to computer vision, including such topics as feature detection, image segmentation, motion estimation, object recognition, and 3D shape reconstruction through stereo, photometric stereo, and structure from motion.4 units.


Required Text: Introductory Techniques for 3-D Computer Vision, E. Trucco and A. Verri, Prentice Hall, 1998.


Prerequisites: Linear algebra and Multivariable calculus (e.g., Math 20A & 20F), data structure/algorithms (e.g., CSE100), a good working knowledge of C,C++, or Matlab programming.


            Assignments:     45%

            Midterm:          20%

            Final Exam:       35%

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.







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




Link to lecture notes



Intro to Computer Vision / T&V Chapter 1


Human Visual System


Image Formation, T&V pp.15-19


Color, Color is well-treated in many image-processing texts.Some reasonable on-line sources include: Basics of Color, A FAQ on Color


Segmentation & Binary images, Horn Chapters 3&4, available at e-reserves See on-line resource


Binary Images &/Filtering


Filtering, T&V pp. 55-63


Canny Edge detection, T&V 67-81


Curves, Hough Transforms, T&V, pp. 97-100


Intro to Shape-from-x, MidtermReview


May 6



Photometric Stereo ,T&V pp. 140-171


Stereo I,  T&V pp. 140-171


Stereo II


Epipolar Geometry


 Discrete structure from Motion , T&V pp.195-202, 208-211


Optical Flow, T&V pp. 178-194


Statistical Pattern Recognition, T&V pp. 248, 262-269



Model-based recognition/Final Exam Review, , T&V 249-261

Notes and links

Programming languages:For any work in this course, you can use any language.We’ve often found it convenient to program many image operations in Matlab. . Click here for Serge Belongie’sMatlab resource links.


Another excellent textbook: Computer Vision -- A Modern Approach, Forsyth and Ponce

CV-online: A useful on-line compendium of Computer Vision sources

Handy Math reference:MathWorld


Some other useful vision links