EE/CSE 576: Image Understanding

Spring 1999

Course Syllabus

Purpose of Course: To introduce the topic of Computer Vision to graduate students. The course will discuss all three levels of computer vision: early processing, mid-level vision or feature extraction, and high-level vision or recognition. We will cover some basic material, but will emphasize state-of-the-art techniques and advanced applications.

Text: New Computer Vision Textbook, by Shapiro and Stockman. Hot off the presses, in fact, it hasn't even gotten to the real presses. Chapters will be handed out, and latest versions put on the web. Comments are welcome. It is almost complete, and we'd like to finish it this quarter.

Also, both Vol. 1 and Vol. 2 of the 1992 Haralick and Shapiro text Computer and Robot Vision should be on reserve in the library as is the Jain, Kasturi, and Schunk text, it Machine Vision. This latter text is good reading for students who have little or no previous background in computer vision / image processing.

Programming Language: We have put together a set of C programs for some important low-mid level operations that we often use in 3D object recognition. These will available for downloading from the course web. Students should be able to write their own C/C++ programs to add additional capabilities as needed.

Project: Each student will propose, design, and implement a program that does some kind of machine vision. Possible topics will be discussed in class. The project is geared to take 4-5 weeks and requires a 5-10 page report describing the program and the results.

Topics to Cover:

The topics I expect to cover, grouped into the appropriate chapters in the book, are given below. We will not cover every topic in every chapter, but everything written so far is listed to give you the whole picture.

1. Basics

Ch1. Introduction
Ch2. Imaging and Image Representation
Ch3. Binary Image Analysis
Ch4. Pattern Recognition Concepts*

2. Features for Recognition

Ch5. Filtering and Enhancing Images (just for edge-finding!)
Ch6. Color
Ch7. Texture
Ch8. Content-Based Image Retrieval*
Ch9. Motion
Ch10. Image Segmentation*

3. Recognition and Matching

Ch11. Matching in 2D*
Ch12. Perceiving 3D from 2D Images*
Ch13. 3D Sensing*
Ch14. 3D Models and Matching*

* Research areas in which I work.

Evaluation: The grades will be based on a combination of small homework sets, midterm, final, and project. Projects will be due on the last day of class, so I have ample time to grade them.

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