Energy Minimization Methods in Computer Vision and Pattern Recognition [[electronic resource] ] : 5th International Workshop, EMMCVPR 2005, St. Augustine, FL, USA, November 9-11, 2005, Proceedings / / edited by Anand Rangarajan, Baba Vemuri, Alan L. Yuille

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005
• Edizione: 1st ed. 2005.
• Descrizione fisica: 1 online resource (XII, 666 p.)
• Disciplina: 006.3/7
• Soggetto topico: Optical data processing; Pattern recognition; Artificial intelligence; Computer graphics; Algorithms; Computers; Image Processing and Computer Vision; Pattern Recognition; Artificial Intelligence; Computer Graphics; Algorithm Analysis and Problem Complexity; Computation by Abstract Devices
• Persona (resp. second.): RangarajanAnand; VemuriBaba; YuilleAlan L
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and indexes.
• Nota di contenuto: Probabilistic and Informational Approaches -- Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application -- A Computational Approach to Fisher Information Geometry with Applications to Image Analysis -- Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering -- Concurrent Stereo Matching: An Image Noise-Driven Model -- Color Correction of Underwater Images for Aquatic Robot Inspection -- Bayesian Image Segmentation Using Gaussian Field Priors -- Handling Missing Data in the Computation of 3D Affine Transformations -- Maximum-Likelihood Estimation of Biological Growth Variables -- Deformable-Model Based Textured Object Segmentation -- Total Variation Minimization and a Class of Binary MRF Models -- Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study -- Combinatorial Approaches -- Probabilistic Subgraph Matching Based on Convex Relaxation -- Relaxation of Hard Classification Targets for LSE Minimization -- Linear Programming Matching and Appearance-Adaptive Object Tracking -- Extraction of Layers of Similar Motion Through Combinatorial Techniques -- Object Categorization by Compositional Graphical Models -- Learning Hierarchical Shape Models from Examples -- Discontinuity Preserving Phase Unwrapping Using Graph Cuts -- Retrieving Articulated 3-D Models Using Medial Surfaces and Their Graph Spectra -- Spatio-temporal Segmentation Using Dominant Sets -- Stable Bounded Canonical Sets and Image Matching -- Coined Quantum Walks Lift the Cospectrality of Graphs and Trees -- Variational Approaches -- Geodesic Image Matching: A Wavelet Based Energy Minimization Scheme -- Geodesic Shooting and Diffeomorphic Matching Via Textured Meshes -- An Adaptive Variational Model for Image Decomposition -- Segmentation Informed by Manifold Learning -- One-Shot Integral Invariant Shape Priors for Variational Segmentation -- Dynamic Shape and Appearance Modeling Via Moving and Deforming Layers -- Energy Minimization Based Segmentation and Denoising Using a Multilayer Level Set Approach -- Constrained Total Variation Minimization and Application in Computerized Tomography -- Some New Results on Non-rigid Correspondence and Classification of Curves -- Edge Strength Functions as Shape Priors in Image Segmentation -- Spatio-temporal Prior Shape Constraint for Level Set Segmentation -- A New Implicit Method for Surface Segmentation by Minimal Paths: Applications in 3D Medical Images -- Other Approaches and Applications -- Increasing Efficiency of SVM by Adaptively Penalizing Outliers -- Locally Linear Isometric Parameterization -- A Constrained Hybrid Optimization Algorithm for Morphable Appearance Models -- Kernel Methods for Nonlinear Discriminative Data Analysis -- Reverse-Convex Programming for Sparse Image Codes -- Stereo for Slanted Surfaces: First Order Disparities and Normal Consistency -- Brain Image Analysis Using Spherical Splines -- High-Order Differential Geometry of Curves for Multiview Reconstruction and Matching.
• Titolo autorizzato: Energy Minimization Methods in Computer Vision and Pattern Recognition
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996465728503316
• Lo trovi qui: Univ. di Salerno
• Serie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 3757