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Provides comprehensive coverage of information theory elements implied in modern computer vision and pattern recognition (CVPR) algorithms
Introduces information theory to researchers in CVPR
Additionally, introduces interesting CVPR problems to information theorists
Information Theory (IT) can be highly effective for formulating and designing algorithmic solutions to many problems in Computer Vision and Pattern Recognition (CVPR).
This text introduces and explores the measures, principles, theories, and entropy estimators from IT underlying modern CVPR algorithms, providing comprehensive coverage of the subject through an incremental complexity approach. The authors formulate the main CVPR problems and present the most representative algorithms. In addition, they highlight interesting connections between elements of IT when applied to different problems, leading to the development of a basic research roadmap (the ITinCVPR tube). The result is a novel tool, unique in its conception, both for CVPR and IT researchers, which is intended to contribute as much as possible to a cross-fertilization of both areas.ISBN: 9788132204466
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Pages : 412
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