Geometric Invariance in Computer Vision (Artificial Intelligence) - Hardcover

Mundy, Joseph L.; Zisserman, Andrew

 
9780262132855: Geometric Invariance in Computer Vision (Artificial Intelligence)

Synopsis

These twenty-three contributions focus on the most recent developments in the rapidly evolving field of geometric invariants and their application to computer vision.

The introduction summarizes the basics of invariant theory, discusses how invariants are related to problems in computer vision, and looks at the future possibilities, particularly the notion that invariant analysis might provide a solution to the elusive problem of recognizing general curved 3D objects from an arbitrary viewpoint.

The remaining chapters consist of original papers that present important developments as well as tutorial articles that provide useful background material. These chapters are grouped into categories covering algebraic invariants, nonalgebraic invariants, invariants of multiple views, and applications. An appendix provides an extensive introduction to projective geometry and its applications to basic problems in computer vision.

Joseph Mundy is a Coolidge Fellow at GE Corporate Research & Development. Andrew Zisserman is a Research Fellow in the Robotics Research Group at Oxford University.

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About the Author

Joseph L. Mundy is a Professor of Engineering at Brown University.

Andrew Zisserman is a Science and Engineering Research Council (SERC) Research Fellow in the Department of Computer Science at the University of Edinburgh.

Daniel G. Bobrow is a Research Fellow in the Intelligent Systems Laboratory, Xerox Palo Alto Research Center, editor-in-chief of the Journal of Artificial Intelligence, and Chair of the Governing Board of the Cognitive Science Society.

Michael Brady is Senior Research Scientist at MIT's Artifical Intelligence Laboratory.

Patrick H. Winston is Professor of Electrical Engineering and Computer Science and Director of the Artificial Intelligence Laboratory at MIT.

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