Theoretical Foundations of Computer Vision

New Proposed Course CIS 6930 (Proposed Official Listing CAP 6XXX)
First Offered, Spring 2003

Department of Computer Science, Florida State University

Class time and location

Tuesday and Thursday, 6:35-8:00PM, LOV 103.


Course Home Page
This web page contains the up-to-date information related to this course such as news, announcements, assignments, lecture notes, useful links to resources that are helpful to this class. You are required to visit this web site on a regular basis.

Besides the course home page, an email mailing list and news group will also be established and used to post news and updates.

Course Rationale

Computer vision has evolved into an important field to understand human visual information processing and to design machine vision systems that can interact with their environment flexibly with tremendous civil and military applications. During the last two decades, computer vision has matured with commonly accepted theoretical frameworks to formulate and approach vision problems. The course is a second course in computer vision. With the assumption that students know and understand well elements of vision problems and algorithms, it formulates the vision in a mathematical framework and within the formulations to discuss different approaches and the relationships among those approaches. Thus, it is a critical advanced course for students who are interested in research in computer vision.

Course Description

This course covers theoretical foundations of computer vision. By formulating computer vision as a statistical inference process, computational approaches to vision are presented and analyzed systematically. Topics include Marr’s computational vision paradigm, regularization theory, feature extraction principles, classification algorithms, Bayesian inference framework for vision, pattern theory, and visual learning theories. It concludes with open issues and research directions in computer vision.


CAP 5415 – Principles and Algorithms for Computer Vision, or permission of the instructor.

Course Objectives

Upon successful completion of this course of study a student:

Textbook and Class Materials

2D Object Detection and Recognition: Models, Algorithms, and Networks” (Yali Amit, MIT Press, 2002), recommended.

Elements of Pattern Theory,” (Ulf Grenander, Johns Hopkins University Press, 1996), recommended.

Vision: A Computational Investigation into the Human Representation and Processing of Visual Information” (David Marr, W. H, Freeman and Company, 1982), recommended.

Perception as Bayesian Inference” (David C. Knill and Whitman Richards, Cambridge University Press, 1996), recommended.


In addition to the textbooks, papers and notes from the literature will be distributed along the lectures, including the following journals and conference proceedings:

Student Responsibilities

Attendance is required for this class. Unless you obtain prior consent of the instructor, missing classes will be used as bases for attendance grading. In case that it is necessary to skip a class, students are responsible to make up missing covered materials. Participation of in-class discussions and activities is also required. All submitted assignments and projects must be done by the author. It is a violation of Academic Honor Code to submit other’s work and the instructor and TA of this course take the violations very seriously.

Assignments and Projects

Exercises will be given to help you understand the basic concepts and techniques and need not to be turned in. There will be a term programming project, which can be done in any programming language including Matlab, Java, and C/C++. The project must involve some creativity and novelty. Based on the student’s research interest, a research paper, which can be a literature review or a survey on a particular topic, will be also assigned. There will be a final exam.

Grading Policy

Grades will be determined as follows:






10 %

Term project

25 %

Class participation

10 %

Research Paper

15 %


15 %

Final exam

25 %


Grading will be based on the weighted average as specified above and the following scale will be used (suppose the weighted average is S in 100 scale)







93 £ S


80 £ S < 83


67 £ S < 70


90 £ S < 93


77 £ S < 80


63 £ S < 67


87 £ S < 90


73 £ S < 77


60 £ S < 63


83 £ S < 87


70 £ S < 73


S < 60 


Late Penalties

Assignments are due at the beginning of the class on the due date. Assignments turned in late, but before the beginning of the next scheduled class will be penalized by 10 %. Assignments that are more than one class period late will NOT be accepted.


Submission and Return Policy

All tests/assignments/projects/homework will be returned as soon as possible after grading but no later than two weeks from the due date.


Tentative Schedule

Academic Honor Code

Programming assignments/written assignments/quizzes/exams are to be done individually, unless specified otherwise. It is a violation of the Academic Honor Code to take credit for the work done by other people. It is also a violation to assist another person in violating the Code (See the FSU Student Handbook for penalties for violations of the Honor Code.). The judgment for the violation of the Academic Honor Code will be done by the TA, the instructor and a third part member (another faculty member in the Computer Science Department not involved in this course). Once the judgment is made, the case is closed and no arguments from the involved parties will be heard. Examples of cheating behaviors include:

Penalty for violating the Academic Honor Code: A 0 grade for the particular homework/project/exam and a reduction of one letter grade in the final grade for all parties involved. A report will be sent to the department head for further administrative actions.

Accommodation for Disabilities

Students with disabilities needing academic accommodations should: 1. Register with and provide documentation to the Student Disability Resource Center (SDRC); 2. Bring a letter to the instructor from the SDRC indicating you need academic accommodations. This should be done within the first week of class. This syllabus and other class materials are available in alternative format upon request.

© 2003, Florida State University. Created on January 7, 2003.