1. 1 Computer Vision Instructor: Prof. Sei-Wang Chen, PhD Office: Applied Science Building, Room 101 Communication: Tel: 77346661 E-mail: schen@csie.ntnu.edu.twschen@csie.ntnu.edu.tw Class Hr. : Mon. 2:10PM - 5:00PM Office Hr. : Mon. 10:00AM - 12:00Noon Wed. 10:00AM - 12:00Noon

2. 22 Teaching assistant : Office : Applied Science Building, ITS laboratory (Basement) Telephone : 77346696 E-mail: Office Hrs. :

3. 3 Goal of Course Computer vision is a study attempting to understand and imitate biological vision systems, especially the human vision system, and focuses on the computational techniques of low, mid and high levels vision. This course covers a wide range of research problems encountered within computer vision and provides detailed algorithmic and theoretical treatments for each.

4. 4 Textbook: Computer Vision: A Modern Approach D. A. Forsyth and J. Ponce, 2012 新月圖書公司 周定宥 23317856, 0935337865

5. 5 Contents of the Textbook: Part 1: Image Formation Part 2: Early Vision: Just One Image Part 3: Early Vision: Multiple Images Part 4: Mid-Level Vision Part 5: High-Level Vision Part 6: Applications Part 7: Background Material

6. 6 Part 1: Image Formation Ch. 1: Geometric Camera Models (Chs. 1,2) Ch. 2: Light and Shading (Chs. 4,5) Ch. 3: Color (Ch. 6) Part 2: Early Vision: Just One Image Ch. 4: Linear Filters Ch. 5: Local Image Features Ch. 6: Texture Part 3: Early Vision: Multiple Images Ch. 7: Stereopsis (Ch. 10,11) Ch. 8: Structure from Motion (Chs. 8,12)

7. 7 Part 4: Mid-Level Vision Ch. 9: Segmentation by Clustering Ch. 10: Grouping and Model Fitting Ch. 11: Tracking Part 5: High-Level Vision Ch. 12: Registration Ch. 13: Smooth Surfaces and their Outlines Ch. 14: Range Data Ch. 15: Learning to Classify Ch. 16: Classifying Images

8. 8 Ch. 19: Image-Based Modeling and Rendering Ch. 20: Looking at People Ch. 21: Image Search and Retrieval Ch. 17: Detecting Objects in Images Ch. 18: Object Recognition Part 6: Applications Part 7: Background Material Ch. 22: Optimization Techniques (Ch. 3)

9. 9 Ch. 1 : Cameras Ch. 2 : Geometric Camera Models Ch. 3 : Geometric Camera Calibration Ch. 4 : Radimetry-Measuring Light Ch. 5 : Sources, Shadow, Shading Ch. 6 : Color Ch. 8 : Structure from Motion Ch. 10: The Geometry of Multiple Views Ch. 11: Stereopsis Ch. 12: Affine Structure from Motion

10. 10 Syllabus Week Content 1 Ch1 2 Ch1 3 Ch2 4 Ch2 5 Ch3 6 Ch3 7 Ch4 8 Ch4 9 Examination

11. 11 Week Content 10 Ch5 11 Ch5 12 Ch6 13 Ch6 14 Ch10 15 Ch10 16 Ch11 17 Ch11 18 Presentation

12. 12 Steps for finding the power points of chapters (1) http://www.csie.ntnu.edu.tw/~ipcv/ (2) Professor Sei-Wang Chen ( 陳世旺教授 ) (3) Teaching (4) Computer Vision

13. 13 References: (A) Books (1) Perception by R. Sekuler and R. Blake, 1985 (2) Computer Vision by D. H. Ballard and C. M. Brown, 1982 (3) Image Processing, Analysis, and Machine Vision by M. Sonka, V. Hlavac, and R. Boyle, 1999 (4) Computer Vision by L. G. Shapiro and G. C. Stockman, 2001 (5) Handbook of Computer Vision Algorithms in Image Algebra by G. X. Ritter and J. N. Wilson, 2001 (6) Computer Vision, A Modern Approach by D. A. Forsyth and J. Ponce, 2003 (7) Digital Geometry, Geometric Methods for Digital Picture Analysis by R. Klette and A. Rosenfeld, 2004 (8) Handbook of Mathematical Models in Computer Vision Ed. by N. Paragios, Y. Chen, and O. Faugeras, 2006

14. 14 (B) Journals (1) IEEE Trans. on Pattern Analysis and Machine Intelligence (2) Int’l Journal of Computer Vision (3) IEEE Trans. on Image Processing (4) Computer Vision and Image Understanding (5) Pattern Recognition (C) Conferences (1) Int’l Conference on Computer Vision (ICCV) (2) Int’l Conference on Pattern Recognition (ICPR) (3) Int’l Conference on Image Processing (ICIP) (4) Int’l Conference on Computer Vision and Pattern Recognition (CVPR)

15. 15 (1) Prepare the assignment file Content: (i) Problem statement (ii) (a) General assignment – Answer (b) Project assignment – (1) Input/Output data (2) Source code (3) Comments File Name: NAME_hw#, e.g., 陳世旺.hw1 Assignment Submission

16. 16 (2) Submit the file to: (i) ftp://140.122.184.4 (ii) User ID: students; Password: 123456 (iii) 點選 “disk1” 資料夾 點選 “CV 作業 ” 資料夾 點選 “HW#” 資料夾 (iv) 上傳作業 作業繳交時間在下一次上課前

17. 17 Evaluation: Interaction 20% Homework 30% Examination 20% Presentation 30% Late homeworks and reports will not be accepted Plagiarism is definitely not allowed