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Computer Vision and Machine Learning with RGB-D Sensors / / edited by Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang
| Computer Vision and Machine Learning with RGB-D Sensors / / edited by Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 006.37 |
| Collana | Advances in Computer Vision and Pattern Recognition |
| Soggetto topico |
Optical data processing
Artificial intelligence User interfaces (Computer systems) Image Processing and Computer Vision Artificial Intelligence User Interfaces and Human Computer Interaction |
| ISBN | 3-319-08651-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I: Surveys -- 3D Depth Cameras in Vision: Benefits and Limitations of the Hardware -- A State-of-the-Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets -- Part II: Reconstruction, Mapping and Synthesis -- Calibration Between Depth and Color Sensors for Commodity Depth Cameras -- Depth Map Denoising via CDT-Based Joint Bilateral Filter -- Human Performance Capture Using Multiple Handheld Kinects -- Human Centered 3D Home Applications via Low-Cost RGBD Cameras -- Matching of 3D Objects Based on 3D Curves -- Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinects -- Part III: Detection, Segmentation and Tracking -- RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons -- RGB-D Human Identification and Tracking in a Smart Environment -- Part IV: Learning-Based Recognition -- Feature Descriptors for Depth-Based Hand Gesture Recognition -- Hand Parsing and Gesture Recognition with a Commodity Depth Camera -- Learning Fast Hand Pose Recognition -- Real time Hand-Gesture Recognition Using RGB-D Sensor. |
| Record Nr. | UNINA-9910298987103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
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 | ||
| ||
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 | ||
| ||