電腦視覺
Computer Vision
| 節 | 週二 |
|---|---|
3 10:10–11:00 | 電腦視覺 EDB27 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
The goal of this course is to introduce the essential concepts and techniques of computer vision, from camera models, feature extraction, segmentation to depth recovery. Advanced topics, such as learning-based methods or modern image segmentation, will also be introduced.
Computer programming with C/C++ or Python, essential knowledge bout data structure and algorithms, calculus, and matrix computation
# EMI (English as a medium of instruction) course: Lectures, slides, announcements and so on are in English. Students are still welcome to discuss or ask questions in Mandarin Chinese. # The official course page is on E3
(Provisional) * Programming homework 30~60% * Term project 30~60% * Quiz 0~15% * Class participation 0~10% or bonus
- Image formation and models
- Features
- 3D reconstruction
- Advanced topics
- Presentation and demo
| 週次 | 主題 |
|---|---|
| 第 1 週 | Overview of computer vision |
| 第 2 週 | TransformationGeometric camera model |
| 第 3 週 | Illumination and shading |
| 第 4 週 | Convolution and filtering |
| 第 5 週 | Texture and key points |
| 第 6 週 | key points and matching |
| 第 7 週 | Image alignment and panorama |
| 第 8 週 | Epipolar geometry |
| 第 9 週 | Structure from motion |
| 第 10 週 | Camera calibration |
| 第 11 週 | Depth map estimation |
| 第 12 週 | Advanced topics |
| 第 13 週 | Exam |
| 第 14 週 | Paper study and project proposal |
| 第 15 週 | Paper study and project proposal |
| 第 16 週 | Presentation and demo (or flexible learning week) |
| 第 17 週 | Flexible learning week (or presentation and demo) |
| 第 18 週 | Flexible learning week |
Text book: * David A. Forsyth and Jean Ponce, Computer Vison: A Modern Approach, Prentice Hall, New Jersey, (2012 or 2003 version) Reference book: * Richard Szeliski, Computer Vision: Algorithms and Applications, Springer Verlag London, 2011.
- 地點
- EC704
- 時間
- To be announced
- 聯絡方式
- Phone ext: 56684 Email: ichenlin@cs.nycu.edu.tw