課程名稱 |
機器人視覺 Robot Vision |
開課學期 |
109-2 |
授課對象 |
工學院 機械工程學系 |
授課教師 |
林峻永 |
課號 |
ME5043 |
課程識別碼 |
522 U6180 |
班次 |
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學分 |
3.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期一2,3,4(9:10~12:10) |
上課地點 |
新404 |
備註 |
總人數上限:50人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1092ME5043_ |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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課程概述 |
This class is designed for the graduate or junior/ senior engineering students. Students will learn the image processing, model-based vision, camera model, calibration, pose estimation, stereo vision, and neural network (and AI) for robot vision. |
課程目標 |
Design of algorithms for robotic vision systems for automation, manufacturing, and the service industries, image processing, optics, illumination, and feature representation. |
課程要求 |
Engineering Mathematics |
預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
待補 |
參考書目 |
1. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, 4th Edition, 2018.
2. R. Gonzalez, R. Woods, and S. Eddins, Digital Image Processing using Matlab, 2nd ed., Prentice Hall, 2009.
3. D. H. Ballard and C. M. Brown, Computer Vision, Prentice Hall. 1982.
4. B. K. P. Horn, Robot Vision, MIT Press. 1986.
5. N. Zuech, Applying Machine Vision, Wiley Interscience. 1988.
6. R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, V1 & 2, Addison Wesley. 1992.
7. F. van der Heijden, Image Based Measurement Systems, John Wiley and Sons, 1995.
8. E. R. Davies, Computer and Machine Vision: Theory, Algorithm, & Practicalities, 4th ed., Acad. Press, 2012.
9. Linda G. Shapiro and George C. Stockman, Machine Vision, Prentice Hall, 2001.
10. D. A. Forsyth, and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall. 2nd ed., 2011.
11. R. Szeliski, Computer Vision: Algorithms and Applications, Springer-Verlag, London, 2011. |
評量方式 (僅供參考) |
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週次 |
日期 |
單元主題 |
第1週 |
2/22 |
Introduction to robot vision
Low-level image processing, Introduction to Matlab for robot vision |
第2週 |
3/01 |
Holiday |
第3週 |
3/08 |
Low-level image processing, Introduction to OpenCV |
第4週 |
3/15 |
Model-based vision I: Hough transform
Morphological operation |
第5週 |
3/22 |
Model-based vision I:
Curvature method, Project proposal
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第6週 |
3/29 |
Model-based vision II:
Featuring matching and selection, Image degradation and restoration
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第7週 |
4/05 |
Holiday |
第8週 |
4/12 |
1st Exam |
第9週 |
4/19 |
Frequency Analysis
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第10週 |
4/26 |
Biologically inspired vision:
Neural network |
第11週 |
5/03 |
Geometric methods I:
Camera calibration
Project preview demonstration |
第12週 |
5/10 |
Geometric methods II:
Hand eye calibration, Pose estimation |
第13週 |
5/17 |
Online lecture |
第14週 |
5/24 |
Online lecture |
第15週 |
5/31 |
Online lecture |
第16週 |
6/07 |
2nd Exam |
第17週 |
6/14 |
Holiday |
第18週 |
6/21 |
Final project presentation |
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