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Markov random fields for vision and image processing [[electronic resource] /] / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
Markov random fields for vision and image processing [[electronic resource] /] / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
Pubbl/distr/stampa Cambridge, Mass., : MIT Press, c2011
Descrizione fisica 1 online resource (472 p.)
Disciplina 006.3/70151
Altri autori (Persone) BlakeAndrew <1956->
KohliPushmeet
RotherCarsten
Soggetto topico Image processing - Mathematics
Computer graphics - Mathematics
Computer vision - Mathematics
Markov random fields
Soggetto genere / forma Electronic books.
ISBN 1-283-25865-X
9786613258656
0-262-29835-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover ; Contents; 1 Introduction to Markov Random Fields; I Algorithms for Inference of MAP Estimates for MRFs; 2 Basic Graph Cut Algorithms; 3 Optimizing Multilabel MRFs Using Move-Making Algorithms; 4 Optimizing Multilabel MRFs with Convex and Truncated Convex Priors; 5 Loopy Belief Propagation, Mean Field Theory, and Bethe Approximations; 6 Linear Programming and Variants of Belief Propagation; II Applications of MRFs, including Segmentation; 7 Interactive Foreground Extraction; 8 Continuous-Valued MRF for Image Segmentation; 9 Bilayer Segmentation of Video
10 MRFs for Superresolution and Texture Synthesis11 A Comparative Study of Energy Minimization Methods for MRFs; III Further Topics: Inference, Parameter Learning, and Continuous Models; 12 Convex Relaxation Techniques for Segmentation, Stereo, and Multiview Reconstruction; 13 Learning Parameters in Continuous-Valued Markov Random Fields; 14 Message Passing with Continuous Latent Variables; 15 Learning Large-Margin Random Fields Using Graph Cuts; 16 Analyzing Convex Relaxations for MAP Estimation; 17 MAP Inference by Fast Primal-Dual Linear Programming
18 Fusion-Move Optimization for MRFs with an Extensive Label SpaceIV Higher-Order MRFs and Global Constraints; 19 Field of Experts; 20 Enforcing Label Consistency Using Higher-Order Potentials; 21 Exact Optimization for Markov Random Fields with Nonlocal Parameters; 22 Graph Cut-Based Image Segmentation with Connectivity Priors; V Advanced Applications of MRFs; 23 Symmetric Stereo Matching for Occlusion Handling; 24 Steerable Random Fields for Image Restoration; 25 Markov Random Fields for Object Detection; 26 SIFT Flow; 27 Unwrap Mosaics; Bibliography; Contributors; Index
Record Nr. UNINA-9910456890503321
Cambridge, Mass., : MIT Press, c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Markov random fields for vision and image processing / / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
Markov random fields for vision and image processing / / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
Pubbl/distr/stampa Cambridge, Mass., : MIT Press, ©2011
Descrizione fisica 1 online resource (472 p.)
Disciplina 006.3/70151
Altri autori (Persone) BlakeAndrew <1956->
KohliPushmeet
RotherCarsten
Soggetto topico Image processing - Mathematics
Computer graphics - Mathematics
Computer vision - Mathematics
Markov random fields
Soggetto non controllato NEUROSCIENCE/Visual Neuroscience
COMPUTER SCIENCE/General
ISBN 1-283-25865-X
9786613258656
0-262-29835-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover ; Contents; 1 Introduction to Markov Random Fields; I Algorithms for Inference of MAP Estimates for MRFs; 2 Basic Graph Cut Algorithms; 3 Optimizing Multilabel MRFs Using Move-Making Algorithms; 4 Optimizing Multilabel MRFs with Convex and Truncated Convex Priors; 5 Loopy Belief Propagation, Mean Field Theory, and Bethe Approximations; 6 Linear Programming and Variants of Belief Propagation; II Applications of MRFs, including Segmentation; 7 Interactive Foreground Extraction; 8 Continuous-Valued MRF for Image Segmentation; 9 Bilayer Segmentation of Video
10 MRFs for Superresolution and Texture Synthesis11 A Comparative Study of Energy Minimization Methods for MRFs; III Further Topics: Inference, Parameter Learning, and Continuous Models; 12 Convex Relaxation Techniques for Segmentation, Stereo, and Multiview Reconstruction; 13 Learning Parameters in Continuous-Valued Markov Random Fields; 14 Message Passing with Continuous Latent Variables; 15 Learning Large-Margin Random Fields Using Graph Cuts; 16 Analyzing Convex Relaxations for MAP Estimation; 17 MAP Inference by Fast Primal-Dual Linear Programming
18 Fusion-Move Optimization for MRFs with an Extensive Label SpaceIV Higher-Order MRFs and Global Constraints; 19 Field of Experts; 20 Enforcing Label Consistency Using Higher-Order Potentials; 21 Exact Optimization for Markov Random Fields with Nonlocal Parameters; 22 Graph Cut-Based Image Segmentation with Connectivity Priors; V Advanced Applications of MRFs; 23 Symmetric Stereo Matching for Occlusion Handling; 24 Steerable Random Fields for Image Restoration; 25 Markov Random Fields for Object Detection; 26 SIFT Flow; 27 Unwrap Mosaics; Bibliography; Contributors; Index
Record Nr. UNINA-9910781666803321
Cambridge, Mass., : MIT Press, ©2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Markov random fields for vision and image processing / / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
Markov random fields for vision and image processing / / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
Pubbl/distr/stampa Cambridge, Mass., : MIT Press, ©2011
Descrizione fisica 1 online resource (472 p.)
Disciplina 006.3/70151
Altri autori (Persone) BlakeAndrew <1956->
KohliPushmeet
RotherCarsten
Soggetto topico Image processing - Mathematics
Computer graphics - Mathematics
Computer vision - Mathematics
Markov random fields
Soggetto non controllato NEUROSCIENCE/Visual Neuroscience
COMPUTER SCIENCE/General
ISBN 1-283-25865-X
9786613258656
0-262-29835-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover ; Contents; 1 Introduction to Markov Random Fields; I Algorithms for Inference of MAP Estimates for MRFs; 2 Basic Graph Cut Algorithms; 3 Optimizing Multilabel MRFs Using Move-Making Algorithms; 4 Optimizing Multilabel MRFs with Convex and Truncated Convex Priors; 5 Loopy Belief Propagation, Mean Field Theory, and Bethe Approximations; 6 Linear Programming and Variants of Belief Propagation; II Applications of MRFs, including Segmentation; 7 Interactive Foreground Extraction; 8 Continuous-Valued MRF for Image Segmentation; 9 Bilayer Segmentation of Video
10 MRFs for Superresolution and Texture Synthesis11 A Comparative Study of Energy Minimization Methods for MRFs; III Further Topics: Inference, Parameter Learning, and Continuous Models; 12 Convex Relaxation Techniques for Segmentation, Stereo, and Multiview Reconstruction; 13 Learning Parameters in Continuous-Valued Markov Random Fields; 14 Message Passing with Continuous Latent Variables; 15 Learning Large-Margin Random Fields Using Graph Cuts; 16 Analyzing Convex Relaxations for MAP Estimation; 17 MAP Inference by Fast Primal-Dual Linear Programming
18 Fusion-Move Optimization for MRFs with an Extensive Label SpaceIV Higher-Order MRFs and Global Constraints; 19 Field of Experts; 20 Enforcing Label Consistency Using Higher-Order Potentials; 21 Exact Optimization for Markov Random Fields with Nonlocal Parameters; 22 Graph Cut-Based Image Segmentation with Connectivity Priors; V Advanced Applications of MRFs; 23 Symmetric Stereo Matching for Occlusion Handling; 24 Steerable Random Fields for Image Restoration; 25 Markov Random Fields for Object Detection; 26 SIFT Flow; 27 Unwrap Mosaics; Bibliography; Contributors; Index
Record Nr. UNINA-9910806178703321
Cambridge, Mass., : MIT Press, ©2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui