Energy Minimization Methods in Computer Vision and Pattern Recognition [[electronic resource] ] : 4th International Workshop, EMMCVPR 2003, Lisbon, Portugal, July 7-9, 2003, Proceedings / / edited by Anand Rangarajan, Mário A. T. Figueiredo, Josiane Zerubia

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
• Edizione: 1st ed. 2003.
• Descrizione fisica: 1 online resource (XI, 534 p.)
• Disciplina: 006.3/7
• Soggetto topico: Optical data processing; Pattern recognition; Computers; Algorithms; Artificial intelligence; Computer graphics; Image Processing and Computer Vision; Pattern Recognition; Computation by Abstract Devices; Algorithm Analysis and Problem Complexity; Artificial Intelligence; Computer Graphics
• Persona (resp. second.): RangarajanAnand; FigueiredoMário A. T; ZerubiaJosiane
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Unsupervised Learning and Matching -- Stochastic Search for Optimal Linear Representations of Images on Spaces with Orthogonality Constraints -- Local PCA for Strip Line Detection and Thinning -- Curve Matching Using the Fast Marching Method -- EM Algorithm for Clustering an Ensemble of Graphs with Comb Matching -- Information Force Clustering Using Directed Trees -- Watershed-Based Unsupervised Clustering -- Probabilistic Modelling -- Active Sampling Strategies for Multihypothesis Testing -- Likelihood Based Hierarchical Clustering and Network Topology Identification -- Learning Mixtures of Tree-Unions by Minimizing Description Length -- Image Registration and Segmentation by Maximizing the Jensen-Rényi Divergence -- Asymptotic Characterization of Log-Likelihood Maximization Based Algorithms and Applications -- Maximum Entropy Models for Skin Detection -- Hierarchical Annealing for Random Image Synthesis -- On Solutions to Multivariate Maximum ?-Entropy Problems -- Segmentation and Grouping -- Semi-supervised Image Segmentation by Parametric Distributional Clustering -- Path Variation and Image Segmentation -- A Fast Snake Segmentation Method Applied to Histopathological Sections -- A Compositionality Architecture for Perceptual Feature Grouping -- Using Prior Shape and Points in Medical Image Segmentation -- Separating a Texture from an Arbitrary Background Using Pairwise Grey Level Cooccurrences -- Shape Modelling -- Surface Recovery from 3D Point Data Using a Combined Parametric and Geometric Flow Approach -- Geometric Analysis of Continuous, Planar Shapes -- Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling -- Definition of a Signal-to-Noise Ratio for Object Segmentation Using Polygonal MDL-Based Statistical Snakes -- Restoration and Reconstruction -- Minimization of Cost-Functions with Non-smooth Data-Fidelity Terms to Clean Impulsive Noise -- A Fast GEM Algorithm for Bayesian Wavelet-Based Image Restoration Using a Class of Heavy-Tailed Priors -- Diffusion Tensor MR Image Restoration -- A MAP Estimation Algorithm Using IIR Recursive Filters -- Estimation of Rank Deficient Matrices from Partial Observations: Two-Step Iterative Algorithms -- Contextual and Non-combinatorial Approach to Feature Extraction -- Graphs and Graph-Based Methods -- Generalizing the Motzkin-Straus Theorem to Edge-Weighted Graphs, with Applications to Image Segmentation -- Generalized Multi-camera Scene Reconstruction Using Graph Cuts -- Graph Matching Using Spectral Seriation.
• Titolo autorizzato: Energy Minimization Methods in Computer Vision and Pattern Recognition
• ISBN: 3-540-45063-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996466068203316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Computer Science, . 0302-9743 ; ; 2683