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Markov Random Field Modeling in Image Analysis by Stan Z Li
Markov Random Field Modeling in Image Analysis by Stan Z Li
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Markov Random Field Modeling in Image Analysis

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Description

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; Learning MRF for Classification. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas.
Release date NZ
October 21st, 2010
Author
Audience
  • Professional & Vocational
Edition
Softcover reprint of hardcover 3rd ed. 2009
Illustrations
111 Illustrations, black and white; XXII, 362 p. 111 illus.
Pages
362
Dimensions
156x234x20
ISBN-13
9781849967679
Product ID
9982559

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