電腦視覺
Computer Vision
學期
110-2
學分
3
學分
當期課號
5236
永久課號
IOG5028
開課單位
智慧科學暨綠能學院
授課教師
謝君偉
校區
歸仁
類別
選修
上課時間表
| 節 | 週一 |
|---|---|
5 13:20–14:10 | 電腦視覺 CM214 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
概述
This course discusses the core techniques in computer vision, such as video processing, feature extraction, dimension reduction, 3D reconstruction, and object detection and tracking. The goal is to learn the techniques in computer vision, connect to the industry, and apply them to the smart home, autonomous vehicle, defect detection, security monitoring, medical image, etc. The presentation is required by the end of the semester.
先修科目
無
評分方式
Assignment 40%、Mid-term exam20%、Final exam20%、Report / Presentation 20%
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to Computer Vision. |
| 第 2 週 | Introduction to Camera Models (internal and external parameters). |
| 第 3 週 | Day off 228 Memorial Day |
| 第 4 週 | Edge and Line Detection: introduction to the detection techniques. |
| 第 5 週 | Hough Transform: introduction to camera models. |
| 第 6 週 | Feature Extraction and Matching: introduction to the techniques in feature extraction and matching. |
| 第 7 週 | Object Detection: introduction to the techniques in object detection and boosting. |
| 第 8 週 | Day off |
| 第 9 週 | Mid-term exam |
| 第 10 週 | Object Tracking: introduction to the techniques in mean-shift and particle filter. |
| 第 11 週 | Color Image Processing: introduction to the color image formats. |
| 第 12 週 | Object Segmentation: introduction to the techniques in object segmentation. |
| 第 13 週 | Keypoint extraction and matching: introduction to the techniques in keypoint extraction and matching. |
| 第 14 週 | Gaussian Mixture Model: introduction to the techniques in background subtraction and GMM. |
| 第 15 週 | Depth Estimation and 3D Reconstruction |
| 第 16 週 | Report and Presentation |
| 第 17 週 | Guest Lecturer: a brief introduction to the industry. |
| 第 18 週 | Final exam / Report submission |
教科書
1.G. Shapiro, and G. C. Stockman, Computer vision 2.M. R. Haralick, andL. G. Shapiro, Computer and robot vision