Energy Minimization Methods in Computer Vision and Pattern Recognition de Anand Rangarajan

Energy Minimization Methods in Computer Vision and Pattern Recognition

Anand Rangarajan

Baba Vemuri

Alan L. Yuille

en Limba Engleză Paperback – 31 oct 2005

Constitutes the refereed proceedings of the 5th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2005, in St Augustine, FL, USA, in November 2005. This book consists of 24 papers and 18 poster papers organized in topical sections on different approaches.

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Cuprins

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.