SEDS 536
Image Understanding
This course covers the image processing techniques and approaches for image content analysis. The course content includes memory representation of images, image processing techniques, keypoint extraction and description, image matching and fundamentals of camera geometry.
Course Objectives
The main aim of the course is to familiarize the students with image processing and image content analysis. The course’s target audience is advanced undergraduate and beginning graduate students. The course will play a preparatory role for the graduate courses covering topics such as digital image processing and 3D photography.
Recommended or Required Reading
Computer Vision: Algorithms and Applications, R. Szeliski, 2010 ,Multiple View Geometry in Computer VIsion, R. Hartley and A. Zisserman, 2nd Ed., 2004
Learning Outcomes
1. Apply image analysis techniques to industrial problems
2. Compare different kinds of image content analysis algorithms for a given problem
3. Use the basic image processing algorithms in problem solutions
4. List the basic image processing algorithms and their properties
| Week | Topics |
|---|---|
| 1 | Introduction |
| 2 | Image Representation |
| 3 | Basic Image Processing |
| 4 | Advanced Image Processing |
| 5 | Keypoint Detection and Matching |
| 6 | Planar Projective Geometry |
| 7 | 3D Projective Geometry |
| 8 | Basic Camera Geometry |
| 9 | Epipolar Geometry |
| 10 | Optimization Techniques |
| 11 | Multiview Geometry |
| 12 | Dense Image Features |
| 13 | Object Category Detection |
| 14 | Object Category Detection |
Grading
Midterm 30%
Homework 30%
Final 40%
