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Synopsis
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.
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Présentation de l'éditeur
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.
Présentation de l'éditeur
This detailed book presents a comprehensive study on the use of Markov Random Fields for solving computer vision problems. Various vision models are presented, and this third edition includes the most recent advances with new and expanded sections.
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Markov Random Field Modeling in Image Analysis
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Markov Random Field Modeling in Image Analysis (Paperback)
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Paperback. Etat : new. Paperback. 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. Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781849967679
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Markov Random Field Modeling in Image Analysis (Advances in Computer Vision and Pattern Recognition)
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Markov Random Field Modeling in Image Analysis
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 362 pp. Englisch. N° de réf. du vendeur 9781849967679
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Markov Random Field Modeling in Image Analysis
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive coverage over a broad range of Markov Random Field TheoryProvides the most recent advances in the fieldMarkov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpre. N° de réf. du vendeur 458523835
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Markov Random Field Modeling in Image Analysis
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Markov Random Field Modeling in Image Analysis (Advances in Computer Vision and Pattern Recognition)
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Markov Random Field Modeling in Image Analysis (Advances in Computer Vision and Pattern Recognition)
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Markov Random Field Modeling in Image Analysis
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Etat : New. This detailed book presents a comprehensive study on the use of Markov Random Fields for solving computer vision problems. Various vision models are presented, and this third edition includes the most recent advances with new and expanded sections. Series: Advances in Computer Vision and Pattern Recognition. Num Pages: 384 pages, 111 black & white illustrations, 11 black & white tables, biography. BIC Classification: UYA; UYQP; UYT. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 20. Weight in Grams: 587. . 2010. 3rd ed. Softcover of orig. ed. 2009. Paperback. . . . . N° de réf. du vendeur V9781849967679
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Markov Random Field Modeling in Image Analysis
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