Course Description
This course provides a comprehensive introduction to computer vision. Major topics include image processing, detection and recognition, geometry-based vision, physics-based vision and video analysis. Students will learn basic concepts of computer vision as well as hands on experience to solve real-life vision problems. This course requires familarity with linear algebra and basic probability. Python will be used for all the assignments.
Recommended Textbook
Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer.
Tentative Schedule
| Date | Lecture | Misc |
|---|---|---|
| Image Processing | ||
| Tue Jan 09 | Introduction | |
| Thu Jan 11 | Filtering | |
| Tue Jan 16 | Programming Tutorial | |
| Thu Jan 18 | Fourier Analysis | |
| Tue Jan 23 | Edge Detection | Assignment 1 Out |
| Thu Jan 25 | Hough Transforms | |
| Tue Jan 30 | Generalized Hough Transform | |
| Recognition | ||
| Thu Feb 01 | Harris Corners | |
| Tue Feb 06 | Multi-Scale Detectors | |
| Thu Feb 08 | Feature Descriptors | Assignment 1 Due |
| Tue Feb 13 | Object Recognition | |
| Thu Feb 15 | Bag-of-Words | Assignment 2 Out |
| Tue Feb 20 | Classification | |
| Thu Feb 22 | Classification | |
| Midterm Exam | ||
| Tue Feb 27 | Review | Assignment 3 Out |
| Thu Mar 01 | Mid-Term Exam | |
| Tue Mar 06 | Spring Break; No Class | |
| Thu Mar 08 | Spring Break; No Class | |
| Image Transformations (2D) | ||
| Tue Mar 13 | 2D Transforms | Assignment 2 Due |
| Thu Mar 15 | 2D Alignment; RANSAC | |
| Multi-View Geometry (3D) | ||
| Tue Mar 20 | Pose Estimation and Triangulation | Assignment 4 Out |
| Thu Mar 22 | Epipolar Geometry | |
| Tue Mar 27 | Essential and Fundamental Matrix | Assignment 3 Due |
| Thu Mar 29 | Reconstruction, Stereo Vision | |
| Tue Apr 03 | Applications of N-view geometry | |
| Video Analysis | ||
| Thu Apr 05 | Optical Flow | Assignment 5 Out |
| Tue Apr 10 | Image Registration | Assignment 4 Due |
| Thu Apr 12 | Image Registration | |
| Tue Apr 17 | Tracking | |
| Thu Apr 19 | Tracking | |
| Tue Apr 24 | Temporal Inference | |
| Thu Apr 26 | Kalman Filtering | Assignment 5 Due |