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Computer and Robot Vision II

Computer and Robot Vision II. Chapter 0. Presented by: 傅楸善 & 顏慕帆 0933 373 485 r94922113@ntu.edu.tw 指導教授 : 傅楸善 博士. Course Number: 922 U1200 Credits: 3 Time: Tuesday 6, 7, 8 (2:20PM~5:20PM) Classroom: New CSIE Classroom 107

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Computer and Robot Vision II

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  1. Computer and Robot Vision II Chapter 0 Presented by: 傅楸善 & 顏慕帆 0933 373 485 r94922113@ntu.edu.tw 指導教授: 傅楸善 博士

  2. Course Number: 922 U1200 • Credits: 3 • Time: Tuesday 6, 7, 8 (2:20PM~5:20PM) • Classroom: New CSIE Classroom 107 • Classification: Elective for junior, senior, and graduate students • Prerequisite: Computer Vision (I), or Digital Image Processing • Instructor: Chiou-Shann Fuh • Office: New Computer Science and Information Engineering 327 • Phone: 23625336 ext.327, 23630231 ext. 3232 ext. 327 • Office Hours: Tuesday 11AM~12 noon • Objective: To learn computer and robot vision through extensive course projects DC & CV Lab. NTU CSIE

  3. Textbook: R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, Vol II Addison Wesley, Reading, MA, 1993 • Reference: B. K. P. Horn Robot Vision, MIT Press, Cambridge, MA, 1986 • Reference: R. Jain, R. Kasturi and B. G. Schunck Machine Vision, McGraw-Hill, New York, 1995 • Projects: assigned weekly on first few weeks(20%) and a term project (30%)􀀀 • Examinations: one midterm (20%) and one final (30%) DC & CV Lab. NTU CSIE

  4. Content: • This is the second semester of a fast pace course which covers robot and computer vision. • The first semester covers low-level vision and mostly no reference to three dimensions • This semester covers higher-level techniques: DC & CV Lab. NTU CSIE

  5. 12. Illumination 13. Perspective Projective Geometry 14. Analytic Photogrammetry 15. Motion and Surface Structure from Time Varying Image Sequences 16. Image Matching 17. The Consistent-Labeling Problem 18. Object Models and Matching 19. Knowledge-Based Vision 20. Accuracy 21. Glossary of Computer Vision Terms DC & CV Lab. NTU CSIE

  6. Bibliography • D. H. Ballard and C. M. Brown, Computer Vision, Prentice-Hall, Englewood Cliffs, NJ, 1982. • G. A. Baxes, Digital Image Processing, Wiley, New York,1984. • K. Castleman , Digital Image Processing, Prentice-Hall, Englewood, Cliffs, NJ, 1996. • E. R. Davies, Machine Vision: Theory, Algorithms, Practicalities,2ndEd., Academic Press, San Diego,CA, 1997 • R.C.Gonzalez and R.E. Woods, Digital Image Processing, Addison Wesley, Reading, MA,1992 • EGose,RJohnsonbaugh, and S. Jost, Pattern Recognition and Image Analysis, Prentice-Hall, Englewood Cliffs, NJ, 1996. • A.K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, Englewood Cliffs, NJ, 1990. • J.S.Lim, Two-Dimensional Signal and Image Processing, Prentice-Hall, Englewood Cliffs, NJ, 1990. • D. Marr, Vision, W.H.Freeman, San Francisco,1982. • V. S. Nalwa, A Guided Tour of Computer Vision, Addison Wesley, Reading, MA, 1993. • W. K. Pratt, Digital Image Processing, 2nd ed., Wiley-Interscience, New York, 1991. • R. J. Schalkoff, Digital Image Processing and Computer Vision: An Interduction to Theory and Implementations, Wiley, New York, 1989. • R. J. Schalkoff, Pattern Recognition: Statistical, Structural, and Neural Approaches, Wiley, New York, 1992. DC & CV Lab. NTU CSIE

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