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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

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

slide2
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

slide3
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

slide4

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

slide5
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

bibliography
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