CELEBRATE EARTH WEEK
Save 70% on video training and simulators now through April 27*—use code EARTH. Shop now.
The state-of-the art in computer vision: theory, applications, and programming
Whether you're a working engineer, developer, researcher, or student, this is your single authoritative source for today's key computer vision innovations. Gerard Medioni and Sing Bing Kang present advances in computer vision such as camera calibration, multi-view geometry, and face detection, and introduce important new topics such as vision for special effects and the tensor voting framework. They begin with the fundamentals, cover select applications in detail, and introduce two popular approaches to computer vision programming.
Download the Sample
Chapter related to this title.
I. FUNDAMENTALS IN COMPUTER VISION.
2. Camera Calibration.
Notation and Problem Statement.
Camera Calibration with 3D Objects.
Camera Calibration with 2D Objects: Plane-Based Technique.
Solving Camera Calibration with 1D Objects.
Appendix: Estimating Homography Between Plane and Image.
3. Multiple View Geometry.
Anders Heyden and Marc Pollefeys.
Multiple View Geometry.
Structure and Motion I.
Structure and Motion II.
Dense Depth Estimation.
4. Robust Techniques for Computer Vision.
Robustness in Visual Tasks.
Models and Estimation Problems.
5. The Tensor Voting Framework.
Gérard Medioni and Philippos Mordohai.
Tensor Voting in 2D.
Tensor Voting in 3D.
Tensor Voting in ND.
Application to Computer Vision Problems.
Conclusion and Future Work.
II. APPLICATIONS IN COMPUTER VISION.
6. Image-Based Lighting.
Paul E. Debevec.
Basic Image-Based Lighting.
Advanced Image-Based Lighting.
7. Computer Vision In Visual Effects.
Computer Vision Problems Unique to Film.
Camera Tracking and Structure from Motion.
8. Content-Based Image Retrieval: An Overview.
Theo Gevers and Arnold W. M. Smeulders
Overview of Chapter.
Representation and Indexing.
Similarity and Search.
Interaction and Learning.
9. Face Detection, Alignment, and Recognition.
Stan Z. Li and Juwei Lu.
10. Perceptual Interfaces.
Matthew Turk and Mathias Kölsch
Perceptual Interfaces and HCI.
III. PROGRAMMING FOR COMPUTER VISION.
11. Open Source Computer Vision Library.
Functional Groups: What's Good for What.
Programming Examples Using C/C++.
12. Software Architecture For Computer Vision.
Alexandre R. J. François.
SAI: A Software Architecture Model.
MFSM: An Architectural Middleware.
Download the Index
file related to this title.