ISBN 9788120350601,Computer Vision: A Modern Appoach

Computer Vision: A Modern Appoach



Pearson India

Publication Year 2014

ISBN 9788120350601

ISBN-10 812035060X


Edition 2nd
Number of Pages 792 Pages
Language (English)

Computer Engineering

This Textbook Provides The Most Complete Treatment Of Modern Computer Vision Methods By Two Of The Leading Authorities In The Field. This Accessible Presentation Gives Both A General View Of The Entire Computer Vision Enterprise And Also Offers Sufficient Detail For Students To Be Able To Build Useful Applications. Students Will Learn Techniques That Are Proven To Be Useful By Firsthand Experience, And A Wide Range Of Mathematical Methods.

The Book Is Useful For Advanced Undergraduate And Beginning Postgraduate Students For Their Courses In Computer Vision In The Departments Of Computer Science, Computer Engineering And Electrical Engineering.

New To This Edition

Every Topic Has Been Updated Based On Current Research And Trends In Computer Vision. Chapters Now Contain Guides To Experimental Resources Online.
Simpler, Clearer Treatment Of Mathematical Topics.
Descriptions Of A Broad Range Of Applications, Including Imagebased Modelling And Rendering, Image Search, Building Image Mosaics, Medical Image Registration, Interpreting Range Data, And Understanding Human Activity.
Comprehensive Treatment Of The Modern Features, Particularly Hog And Sift That Drive Applications Ranging From Building Image Mosaics To Object Recognition.
Detailed Treatment Of Modern Image Editing Techniques, Including Removing Shadows, Filling Holes In Images, Noise Removal, And Interactive Image Segmentation.
Comprehensive Treatment Of Modern Object Recognition Techniques.
Detailed Index And A Bibliography That Is As Comprehensive And Uptodate As Possible.
I. Image Formation

1. Geometric Camera Models
2. Light And Shading
3. Color

Ii. Early Vision: Just One Image

4. Linear Filters
5. Local Image Features
6. Texture

Iii. Early Vision: Multiple Images

7. Stereopsis
8. Structure From Motion

Iv. Midlevel Vision

9. Segmentation By Clustering
10. Grouping And Model Fitting
11. Tracking

V. Highlevel Vision

12. Registration
13. Smooth Surfaces And Their Outlines
14. Range Data
15. Learning To Classify
16. Classifying Images
17. Detecting Objects In Images
18. Topics In Object Recognition

Vi. Applications And Topics

19. Imagebased Modeling And Rendering
20. Looking At People
21. Image Search And Retrieval

Vii. Background Material

22. Optimization Techniques.

List Of Algorithms.
About The Author: Jean Ponce, David A Forsyth
Ecole Normale Superieure|University Of Illinois At Urbanachampaign