Description:

Preface.

 Contributors.

1. Introduction.

I. FUNDAMENTALS IN COMPUTER VISION.  

2. Camera Calibration.

Zhengyou Zhang.

Introduction.

Notation and Problem Statement.

Camera Calibration with 3D Objects.

Camera Calibration with 2D Objects: Plane-Based Technique.

Solving Camera Calibration with 1D Objects.

Self-Calibration.

Conclusion.

Appendix: Estimating Homography Between Plane and Image.

Bibliography.

3. Multiple View Geometry. 

 Anders Heyden and Marc Pollefeys.

Introduction.

Projective Geometry.

Tensor Calculus.

Modeling Cameras.

Multiple View Geometry.

Structure and Motion I.

Structure and Motion II.

Autocalibration.

Dense Depth Estimation.

Visual Modeling.

Conclusion.

Bibliography. 

4. Robust Techniques for Computer Vision.

Peter Meer.

Robustness in Visual Tasks.

Models and Estimation Problems.

Location Estimation.

Robust Regression.

Conclusion.

Bibliography. 

5. The Tensor Voting Framework.

Gérard Medioni and Philippos Mordohai.

Introduction.

Related Work.

Tensor Voting in 2D.

Tensor Voting in 3D.

Tensor Voting in ND.

Application to Computer Vision Problems.

Conclusion and Future Work.

Acknowledgments.

Bibliography. 

II. APPLICATIONS IN COMPUTER VISION.

6. Image-Based Lighting. 

 Paul E. Debevec.

Basic Image-Based Lighting.

Advanced Image-Based Lighting.

Image-Based Relighting.

Conclusion.

Bibliography.

7. Computer Vision In Visual Effects. 

 Doug Roble.

Introduction.

Computer Vision Problems Unique to Film.

Feature Tracking.

Optical Flow.

Camera Tracking and Structure from Motion.

The Future.

Bibliography.

8. Content-Based Image Retrieval: An Overview.

Theo Gevers and Arnold W. M. Smeulders

Overview of Chapter.

Image Domains.

Image Features.

Representation and Indexing.

Similarity and Search.

Interaction and Learning.

Conclusion.

Bibliography.

  9. Face Detection, Alignment, and Recognition.

  Stan Z. Li and Juwei Lu.

Introduction.

Face Detection.

Face Alignment.

Face Recognition.

Bibliography. 

10. Perceptual Interfaces.

Matthew Turk and Mathias Kölsch

Introduction.

Perceptual Interfaces and HCI.

Multimodal Interfaces.

Vision-Based Interfaces.

Brain-Computer Interfaces.

Summary.

Bibliography. 

III. PROGRAMMING FOR COMPUTER VISION.

11. Open Source Computer Vision Library.

Gary Bradski.

Overview.

Functional Groups: What's Good for What.

Pictorial Tour.

Programming Examples Using C/C++.

Other Interfaces.

Appendix A.

Appendix B.

Bibliography.

12. Software Architecture For Computer Vision.

Alexandre R. J. François.

Introduction.

SAI: A Software Architecture Model.

MFSM: An Architectural Middleware.

Conclusion.

Acknowledgments.

Bibliography.

Index.