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CSE 152: Introduction to Computer Vision
Spring 2012
Course Information / Course Outline / Assignments / Notes and Links
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Recent
announcements
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(05/30/2012) Assignment 4 is posted
(05/17/2012) Assignment 3 is posted
(04/28/2012) Assignment 2 is posted
(04/19/2012) Optional Discussion Section will be on Mondays at 3-3:50p in Pepper Canyon Hall, Room 120 and will start on 04/23/12.
(04/18/2012) Assignment 1 is posted
Course
Information
- Lecture: Tuesday & Thursday 9:30 - 10:50 AM in WLH 2205
- Final: June 12, 8-11am
- Discussion: Monday 3 - 3:50 PM in Pepper Canyon Hall, Room 120 (Optional)
- Instructor:
Prof. David Kriegman
Office: EBU-3B, Room 4120
Phone: 858-822-2424
Email: kriegman [AT] cs.ucsd.edu
Office Hours: Tue 1:00 - 2:00 pm - TA:
Steve Branson
Email: sbranson [AT] cs.ucsd.edu
Office Hours: Mon 4-5p and Wed 1-2p in EBU3b, Room B240A (CSE Building Basement)
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.
Required Text: Introductory
Techniques for 3-D Computer Vision, E. Trucco and A. Verri, Prentice
Hall, 1998.
Since the text book is out of print, and the
price of used copies have become outrageous, I've been able to place some of
the reading from Trucco and Verri
on Ereserves at http://reserves.ucsd.edu/eres/coursepage.aspx?cid=17658&page=docs#
Also hardcopies of the book will be available on 3-hour reserve. Optional Text:
Computer Vision: Algorithms and Applications, Richard Szeliski.
An older draft of the book, is available at
http://szeliski.org/Book/ Assignment 0 (due 04/12): Here is a PDF file
for Assignment 0. Assignment 1
(due 04/26): hw1.pdf
Turn in a hard
copy in class including your answer to paper-and-pencil questions as well
as the printout of your code and results for programming questions. In addition, please email the TA <sbranson@cs.ucsd.edu> a zip file of your code (see
the Instruction section for more details). Assignment 2
(due 05/11):
hw2.pdf
To turn in your assignment, please email the TA <sbranson@cs.ucsd.edu> a zip file of your report and code (see
the Instruction section for more details). Assignment 3
(due 05/29):
hw3.pdf
To turn in your assignment, please email the TA <sbranson@cs.ucsd.edu> a zip file of your report and code (see
the Instruction section for more details). Assignment 4
(due 06/08):
hw4.pdf
To turn in your assignment, please email the TA <sbranson@cs.ucsd.edu> a zip file of your report and code (see
the Instruction section for more details). **
Tentative syllabus - subject to change. April 3 -
Introduction to Computer Vision [T&V Chapter 1, Sz. 1-28] April 5 -
Human Visual System, Cues and Illusions April 10 -
Image Formation, Cameras, Projections and Rigid-body Transformations
[T&V
Chapter 2, pp. 26-40, Szeliski. pp. 29-58] April 12 -
Rigid-body Transformations, Camera Calibration and Lenses [Szeliski pp.7-90] April 17 -
Radiometry (Lighting and Shading) [T&V Chapter 2, pp. 16-26, Szeliski pp.60-72] April 19 -
Color [Gonzalez
and Woods: Chapter 6, Basics
of Color, An
FAQ on Color] April 24 -
Binary Image Processing [ Link
to Chapter 4 of "Robot Vision" by Horn (e-reserves) ] April 26 -
Filtering [T&V,
Chapter 3, pages 55-63, Szeliski pp. 111-121] May 1 -
Edge Detection [T&V,
pages 67-81, Szeliski pp. 238-249] May 3 -
Hough Transform [T&V,
pp. 97-100, Szeliski pp. 250-257] May 8 -
Generalized Hough Transform + Line Fitting - May 10: Midterm (Sample
midterm questions) May 15 -
Stereo (Introduction) [T&V, pp. 140-171, Szeliski pp. 533-558] May 17 -
Stereo (Epipolar Geometry) May 22 -
Stereo (Window-based methods + Dynamic Programming + Helmholtz) May 24 -
Photometric Stereo [Forsyth and Ponce, Chapter 5, pages 80-86, Szeliski
pp. 580-582 ] May 29 -
Photometric Stereo / Introduction to Structure-From-Motion (SFM)
[T&V, pages
191-198, Szeliski pp. 343-368 ] May 31 -
Recognition (PCA, Eigenfaces and Fisherfaces)
[Szeiliski pp. 655-693, Fisherfaces paper] May 31 -
Recognition, Bayesian Classifiers [T&V, pages 262-270] June 5 -
Appearance-Based Recognition, Motion Field & Optical Flow
[T&V, pages
191-198, Szeliski pp. 381-415] June 12 - Final Exam á Programming
languages: For this course, all programming will be in Matlab.
A short tutorial assignment will provide the introduction. Click here for Serge Belongie's Matlab resource links.
á Some other textbooks
and resources á Some useful links
Last
updated March 29, 2011.
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.
Grading: There will be homework
assignments, a midterm, and a final weighted with the following percentages:
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.
Assignments
Test image for assignment: flag.jpg.
Matlab tutorial
Test image for problem 2: color.bmp
Test images:
coins.png,
hole.png,
ucsd.png,
ball.png,
Images and matlab functions: hw3_files.zip
Yale Face Database: yaleBfaces.zip
Helper function: loadSubset.m
Course
Outline
Notes
and Links
