1 / 17

Computer Vision

This course explores computational techniques in computer vision, with a focus on understanding and imitating human vision systems. It covers various research problems and provides algorithmic and theoretical treatments. Textbook used: "Computer Vision: A Modern Approach" by D. A. Forsyth and J. Ponce.

rloraine
Download Presentation

Computer Vision

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Computer Vision Instructor: Prof. Sei-Wang Chen, PhD Office: Applied Science Building, Room 101 Communication: Tel: 7734-6661 E-mail:schen@csie.ntnu.edu.tw Class Hr. : Mon. 2:20PM - 5:20PM Classroom: B101 Office Hr. : Mon. 10:00AM - 12:00Noon Thur. 2:00PM - 4:00PM

  2. Teaching assistant : Office : Applied Science Building, ITS laboratory (Basement) Telephone : 7734-6696 E-mail: Office Hrs. : 2

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

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

  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. Syllabus Week Content 1 Ch1 2 Ch1 3 Ch2 4 Ch2 5 Ch3 6 Ch3 7 Ch4 8 Ch4 9 Ch5 10

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

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

  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 VisionAlgorithms 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. (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. Assignment Submission • 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

  16. (2) Submit the file to: (i)ftp://140.122.184.4 (ii) 按右鍵, 選登入身份 (iii) 使用者名稱: students; 密碼: 123456 (iv) 點選“disk1”資料夾 點選“CV”資料夾 點選“HW#”資料夾 (v) 上傳作業 作業繳交時間在下一次上課前

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

More Related