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課程名稱 |
機器人視覺
Robot Vision |
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開課學期 |
110-2 |
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授課對象 |
工學院 機械工程學研究所 |
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授課教師 |
黃漢邦 |
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課號 |
ME5043 |
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課程識別碼 |
522 U6180 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期一2,3,4(9:10~12:10) |
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上課地點 |
工綜215 |
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備註 |
與林峻永合授
總人數上限：65人 |
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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 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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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. |
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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. |
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課程要求 |
Engineering Mathematics |
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預期每週課後學習時數 |
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Office Hours |
每週三 13:30~15:30
每週五 13:30~15:30
每週四 13:30~15:30
每週一 13:30~15:30 備註： 周一為 黃漢邦老師
週四、周五為林峻永老師
周三為助教 |
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指定閱讀 |
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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. |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
HW |
25% |
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2. |
1st Exam |
25% |
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3. |
2nd Exam |
25% |
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4. |
Term Project |
25% |
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週次 |
日期 |
單元主題 |
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第1週 |
2/14 |
Introduction to robot vision |
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第2週 |
2/21 |
Overview of Matlab, OpenCV, Yolo |
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第3週 |
2/28 |
Holiday |
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第4週 |
3/7 |
Frequency analysis, Fourier transform
Random process
Image formation and image processing:
Image degradation and restoration
Project proposal |
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第5週 |
3/14 |
Image formation and image processing:
Hough Transform
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第6週 |
3/21 |
Morphological operation |
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第7週 |
3/28 |
1st Exam |
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第8週 |
4/4 |
Holiday |
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第9週 |
4/11 |
Geometric methods: Camera calibration, Hand eye calibration |
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第10週 |
4/18 |
Geometric methods: Pose estimation, Stereo vision |
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第11週 |
4/25 |
Model-based vision: Hough transform, Principle Component Analysis
Project preview demonstration
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第12週 |
5/2 |
Model-based vision: Curvature method, Featuring matching and selection, |
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第13週 |
5/9 |
Biologically inspired vision: Neural network |
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第14週 |
5/16 |
2nd Exam |
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第15週 |
5/23 |
Color vision, Image segmentation |
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第16週 |
5/30 |
Term project presentation |
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第17週 |
6/6 |
Flex supplement teaching week |
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第18週 |
6/13 |
Flex supplement teaching week |
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