Lab Session
CS4243: Computer Vision and Pattern Recognition, AY 2023/24
Introduction
Welcome to the lab session of CS4243 👋!
This course is for undergraduates who are interested in computer vision and its applications. It covers:
- The basic skills needed in handling images and videos.
- The basic theories needed to understand geometrical computer vision.
- Pattern recognition.
- Topics covered in image handling include: contrast stretch, histogram equalization, noise removal, and color space.
- Topics covered in geometrical vision include: affine transform, vanishing points, camera projection models, homography, camera calibration, rotation representations including quaternions, epipolar geometry, binocular stereo, and structure from motion.
- Topics covered for pattern recognition include principal component analysis.
Materials
| Lab | Week | Topic | Slides | Tutorial | Solution |
|---|---|---|---|---|---|
| 1 | 3 | Background and Global Operations | slides |
notebook |
notebook |
| 2 | 4 | Local Operations and Spatial Domain Filtering | slides |
notebook |
notebook |
| 3 | 5 | Filtering in Fourier Domain | slides |
notebook |
notebook |
| 4 | 6 | Texture Analysis | slides |
notebook |
notebook |
| - | 7 | Recess Week 🌴 | - | - | - |
| 5 | 8 (Mon) | GLCM-Based Texture Analysis, Laws Filters | slides |
notebook |
notebook |
| 5 | 8 (Tue) | GLCM-Based Texture Analysis, Laws Filters | slides |
notebook |
notebook |
| 6 | 9 | Optical Flow | slides |
notebook |
notebook |
| 7 | 10 | Deep Learning, Part 1 | slides |
notebook |
notebook |
| 8 | 11 | Deep Learning, Part 2 | slides |
notebook |
notebook |
Contact
- Lingdong Kong: lingdong.kong@u.nus.edu
- Xiao Cao: xiaocao@u.nus.edu
- Weida Liang: weida_liang@u.nus.edu