CSCI 574 Computer Vision
Fall 2009
Instructor
Prof.
Gerard Medioni
Phone
: (213) 740-6440
Email
: csci574@usc.edu
Office
Hours : MW 11:00 - 12:00
Office
Location : PHE 212
Teaching
Assistant
E-mail : kimeunyo.at.usc.edu
Phone : 213-740-0968
Office Hours : TuTh
9:00 - 10:00
Office Location : PHE 226
Weijun Wang
E-mail : weijunw.at.usc.edu
Phone : 213-740-0968
Office Hours : MF 4:00 - 5:00 pm
Office Location : PHE 224
Textbooks
Required:
1. Computer Vision : A
Mordern Approach, D. Forsyth and J. Ponce,
Prentice-Hall, 2001
2. We will also use Computer
Vision: Algorithms and Applications, Richard Szeliski, 2009
References
1. A Guided Tour of Computer Vision, V.
S. Nalwa, Addison Wesley, 1993
2. Robot Vision, B.K.P.
Horn, MIT Press, 1986
3. Multiple View Geometry in Computer Vision, Richard Hartley and Andrew Zisserman, Cambridge University Press, 2000
4. Image Processing, Analysis, and Machine Vision (3rd Edition), Milan Sonka, Vaclav Hlavac, and Roger Boyle, Thomson
Engineering, 2007
5. Pattern Classification (2nd Edition) Richard
O. Duda, Peter E. Hart, and David G.Stork,
Wiley-Interscience, 2000.
6. Emerging Topics in Computer Vision,
Gerard Medioni, Sing Bing Kang, Prentice Hall, 2005.
Prerequisite
1. CSCI 455 or equivalent - Data Structures, good
programming skills. Ability to convert informal
descriptions into computer algorithms. Students must be able to program in C or C++.
2. Basic Mathematics - Knowledge of and ability to
use calculus, analytical solid geometry and
linear algebra (matrix theory) is essential. Knowledge of elementary probability theory will also be needed. If
you have not used these skills for several years, you must be prepared to learn them rapidly.
3. CSCI 561 and
573 (Artifical Intelligence) are
helpful but NOT required.
Course
Objective
The objective of this course is to
understand the basic issues in computer vision and major approaches that address them.
Even though Computer Vision is being used for many practical
applications today, it is still not a "solved" problem. Hence,
definitive solutions are available
only rarely; most of the time, we will discuss alternatives and their
limitations.
After completing the course, the
students may expect to have the knowledge needed to read and understand the more advanced
topics and current research literature, and the ability to start working
in industry or in academic research. However, this course is NOT designed
to be a "cookbook" course that gives just a survey of the methods
needed in "practice", nor will it
cover "commercial" systems in any detail.
Course
Requirement
There will be two exams:
1.
Exam1: Scheduled on October 14(Wed.)
2.
Exam2: on the last day of the class, December 2(Wed.).
Both exams will
be conducted during class hours.
The grade will be based on the Exam 1 and 2, the homework and the
project. The Exam 1 and 2 will count for 20% each, the project will count for
40% and the HW will count for 20% of the course grade.
(i.e,
Exam1(20%) + Exam2(20%) + HW(20%) + Project(40%)(Project 1(20%) + Project
2(20%))
Note that all assignments are considered an integral
part of the course and MUST be completed. Not completing assignments may result
in "F" grade.
Academic
Integrity
The USC Student
Conduct Code prohibits plagiarism. All USC students are responsible for reading and following the Student Conduct
Code, which appears on pp. 83-97 of the
1997- 1998
SCampus.
In this course we encourage students to study together. This
includes discussing general strategies to be used for individual assignments. However, all
work submitted for the class is to be done individually, unless an assignment specifies otherwise.
Some examples of what is not allowed by the conduct code: copying
all or part of someone else's work, and submitting it as your own; giving another student
in the class a copy of your assignment solution; consulting with another student during an
exam. If you have questions
about what is allowed, please discuss it with the instructor.
Violations of the Student Conduct Code will be filed with the
Office of Student Conduct, and appropriate sanctions will be given.
Programming
Facility
A software library of basic image processing algorithms, called OpenCV, will be used in programming assignments; this
library is available for free download for educational purpose. This library is
available for MS Windows and Linux; however, we will only provide
TA support for the windows version. Students may choose to complete assignments using
USC computer facilities or their own PCs. OpenCV can
be downloaded here.
Other useful links for OpenCV:
Active forum: OpenCV at
YahooGroups
Tutorials and Links: OpenCV Wiki
Syllabus
FP(Forsyth, Ponce Computer
Vision a Modern Approach) and RS(Szeliski Computer Vision: Algorithms and
Applications )