{"text_format":"5","workbook":"xls","n_sheets":1,"sheets":["report2"],"props":{"last_modified_by":"sharecat"},"not_rendered":{"external_links":1,"defined_names":1},"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":26,"n_cols":5,"rows_kept":26,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[9,2,9,3],[20,2,20,3],[21,2,21,3],[24,2,24,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996465647803316"]
[null,null,"Titolo",null,"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"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009"]
[null,null,"ISBN",null,"3-642-03641-4"]
[null,null,"Edizione",null,"[1st ed. 2009.]"]
[null,null,"Descrizione fisica",null,"1 online resource (X, 494 p.)"]
[null,null,"Collana",null,"Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 5681"]
[null,null,"Disciplina",null,"006.6"]
[{"$nulls":4},"006.37"]
[null,null,"Soggetti",null,"Optical data processing"]
[{"$nulls":4},"Pattern recognition"]
[{"$nulls":4},"Computer software—Reusability"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Image Processing and Computer Vision"]
[{"$nulls":4},"Pattern Recognition"]
[{"$nulls":4},"Performance and Reliability"]
[{"$nulls":4},"Algorithm Analysis and Problem Complexity"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[{"$nulls":3},"Livello bibliografico","Monografia"]
[{"$nulls":3},"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Discrete Optimization and Markov Random Fields -- Multi-label Moves for MRFs with Truncated Convex Priors -- Detection and Segmentation of Independently Moving Objects from Dense Scene Flow -- Efficient Global Minimization for the Multiphase Chan-Vese Model of Image Segmentation -- Bipartite Graph Matching Computation on GPU -- Pose-Invariant Face Matching Using MRF Energy Minimization Framework -- Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction -- General Search Algorithms for Energy Minimization Problems -- Partial Differential Equations -- Complex Diffusion on Scalar and Vector Valued Image Graphs -- A PDE Approach to Coupled "]
[{"$nulls":4},"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."]