CS 482
Computer Vision

Time/Location: Monday 4:30-7:10,   Robinson B203
Instructor: Dr. Jana Kosecka
Office: 4444, Research II
email: kosecka@cs.gmu.edu
Course website http://cs.gmu.edu/~kosecka/cs482/

This course will cover essentials of computer vision. We will learn basic principles of image formation, image processing algorithms and different algorithms for 3D reconstruction and recognition from single or multiple images (video). Apllications to 3D modelling, video analysis, video surveillance, object recognition and vision based control will be discussed.  

This course is of interest to anyone seeking to process images or camera information, or to acquire a general background in issues related to real-world perception, image processing, object and scene recognition and multi-view geometry

Schedule, Homeworks, Handouts

Grading Homeworks (about every 2 weeks) 40% Midterm: 30% Final project: 30%
Prerequisites linear algebra, calculus
Lecture Materials Lecture slides, lecture notes provided by instructor


Recommended Textbooks

  • Invitation to 3D Vision: From Images to Geometric Models: Y. Ma, S. Soatto, J. Kosecka and S. Sastry
  • Introductory Techniques for 3D computer Vision. E. Trucco and A. Verri, Prentice-Hall, 1998
  • Computer Vision: A Modern Approach: D. Forsythe and J. Ponce, Prentice-Hall, 2003
  • Computer Vision: Stockman and Shapiro, Prentice Hall.

    • Required Software

    Matlab, OpenCV. Homeworks will require using Matlab and OpenCV. You can buy a student version in Johnson center or use it remotely from ITE labs. OpenCV is an C/C++ open source computer vision library.

    Course Outcomes

    Basic knowledge of image formation process
    Basic knowledge of image processing techniques for color and gray level images: edge detection, corner detection, segmentation
    Basics of video processing, motion computation and 3D vision and geometry
    Ability to implement basic vision algorithms in Matlab and use OpenCV (open source computer vision library)
    Ability to apply the appropriate technique to a problem, write a project report and present the results in class.