Energy Minimization Methods in Computer Vision and Pattern Recognition [[electronic resource] ] : 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009, Proceedings / / edited by Daniel Cremers, Yuri Boykov, Andrew Blake, Frank R. Schmidt

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
• Edizione: 1st ed. 2009.
• Descrizione fisica: 1 online resource (X, 494 p.)
• Disciplina: 006.6; 006.37
• Soggetto topico: Optical data processing; Pattern recognition; Computer software—Reusability; Algorithms; Data mining; Image Processing and Computer Vision; Pattern Recognition; Performance and Reliability; Algorithm Analysis and Problem Complexity; Computer Imaging, Vision, Pattern Recognition and Graphics; Data Mining and Knowledge Discovery
• Persona (resp. second.): CremersDaniel; BoykovYuri; BlakeAndrew; SchmidtFrank R
• Note generali: Includes index.
• Nota di contenuto: Discrete Optimization and Markov Random Fields -- Multi-label Moves for MRFs with Truncated Convex Priors -- Detection and Segmentation of Independently Moving Objects from Dense Scene Flow -- Efficient Global Minimization for the Multiphase Chan-Vese Model of Image Segmentation -- Bipartite Graph Matching Computation on GPU -- Pose-Invariant Face Matching Using MRF Energy Minimization Framework -- Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction -- General Search Algorithms for Energy Minimization Problems -- Partial Differential Equations -- Complex Diffusion on Scalar and Vector Valued Image Graphs -- A PDE Approach to Coupled Super-Resolution with Non-parametric Motion -- On a Decomposition Model for Optical Flow -- A Schrödinger Wave Equation Approach to the Eikonal Equation: Application to Image Analysis -- Computing the Local Continuity Order of Optical Flow Using Fractional Variational Method -- A Local Normal-Based Region Term for Active Contours -- Segmentation and Tracking -- Hierarchical Pairwise Segmentation Using Dominant Sets and Anisotropic Diffusion Kernels -- Tracking as Segmentation of Spatial-Temporal Volumes by Anisotropic Weighted TV -- Complementary Optic Flow -- Parameter Estimation for Marked Point Processes. Application to Object Extraction from Remote Sensing Images -- Three Dimensional Monocular Human Motion Analysis in End-Effector Space -- Robust Segmentation by Cutting across a Stack of Gamma Transformed Images -- Shape Optimization and Registration -- Integrating the Normal Field of a Surface in the Presence of Discontinuities -- Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration without Correspondence -- Geodesics in Shape Space via Variational Time Discretization -- Image Registration under Varying Illumination: Hyper-Demons Algorithm -- Hierarchical Vibrations: A Structural Decomposition Approach for Image Analysis -- Inpainting and Image Denoising -- Exemplar-Based Interpolation of Sparsely Sampled Images -- A Variational Framework for Non-local Image Inpainting -- Image Filtering Driven by Level Curves -- Color Image Restoration Using Nonlocal Mumford-Shah Regularizers -- Reconstructing Optical Flow Fields by Motion Inpainting -- Color and Texture -- Color Image Segmentation in a Quaternion Framework -- Quaternion-Based Color Image Smoothing Using a Spatially Varying Kernel -- Locally Parallel Textures Modeling with Adapted Hilbert Spaces -- Global Optimal Multiple Object Detection Using the Fusion of Shape and Color Information -- Statistics and Learning -- Human Age Estimation by Metric Learning for Regression Problems -- Clustering-Based Construction of Hidden Markov Models for Generative Kernels -- Boundaries as Contours of Optimal Appearance and Area of Support.
• Titolo autorizzato: Energy Minimization Methods in Computer Vision and Pattern Recognition
• ISBN: 3-642-03641-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996465647803316
• Lo trovi qui: Univ. di Salerno
• Serie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 5681