198:534   Computer Vision

Fall 2007

 

 

 

Instructor: Ahmed Elgammal -- email: elgammal - cs

Office: Core 316

 

Office hours: Friday 2:30-4:30pm

 

Regular class time: Wed 6:40-9:30pm  HLL-254

 

Detailed Syllabus  

 

Lectures’ slides and other materials are at the “…/materials.htm” web page.

 

Overview:

This is a basic graduate-level computer vision course that intends to cover a variety of fundamental computer vision topics to get you acquainted with the field.

Topics: [Course outlines]

Image Formation: Cameras, Geometric camera models, Calibration, Radiometry, Color.

Early Vision: Linear filters, Edge detection, Texture, Geometry of multiple views.

Mid-level Vision: Motion, Segmentation, and Tracking.

High-Level Vision: Model-based vision, Object recognition, Pose estimation.

 

 

 

 

Recommended Background:

Linear algebra and basic statistics. 

Familiarity with Matlab programming

Textbook

"Computer Vision: A Modern Approach"

By David Forsyth and Jean Ponce

Prentice Hall 2002

ISBN 0-13-085198-1

 

Other references:

 

 

Course Load

§       Homework assignments: (70%) 4-6 assignments, which might contain some Matlab programming.

§       Exams: Midterm (30%)  in the second half of the semester.

 

 

 

 

Homework assignments: