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Energy Minimization Methods in Computer Vision and Pattern Recognition
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Table of Contents

Probabilistic Models and Estimation.- A Double-Loop Algorithm to Minimize the Bethe Free Energy.- A Variational Approach to Maximum a Posteriori Estimation for Image Denoising.- Maximum Likelihood Estimation of the Template of a Rigid Moving Object.- Metric Similarities Learning through Examples: An Application to Shape Retrieval.- A Fast MAP Algorithm for 3D Ultrasound.- Designing the Minimal Structure of Hidden Markov Model by Bisimulation.- Relaxing Symmetric Multiple Windows Stereo Using Markov Random Fields.- Matching Images to Models — Camera Calibration for 3-D Surface Reconstruction.- A Hierarchical Markov Random Field Model for Figure-Ground Segregation.- Articulated Object Tracking via a Genetic Algorithm.- Image Modelling and Synthesis.- Learning Matrix Space Image Representations.- Supervised Texture Segmentation by Maximising Conditional Likelihood.- Designing Moiré Patterns.- Optimization of Paintbrush Rendering of Images by Dynamic MCMC Methods.- Illumination Invariant Recognition of Color Texture Using Correlation and Covariance Functions.- Clustering, Grouping, and Segmentation.- Path Based Pairwise Data Clustering with Application to Texture Segmentation.- A Maximum Likelihood Framework for Grouping and Segmentation.- Image Labeling and Grouping by Minimizing Linear Functionals over Cones.- Grouping with Directed Relationships.- Segmentations of Spatio-Temporal Images by Spatio-Temporal Markov Random Field Model.- Highlight and Shading Invariant Color Image Segmentation Using Simulated Annealing.- Edge Based Probabilistic Relaxation for Sub-pixel Contour Extraction.- Two Variational Models for Multispectral Image Classification.- Optimization and Graphs.- An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision.- ADiscrete/Continuous Minimization Method in Interferometric Image Processing.- Global Energy Minimization: A Transformation Approach.- Global Feedforward Neural Network Learning for Classification and Regression.- Matching Free Trees, Maximal Cliques, and Monotone Game Dynamics.- Efficiently Computing Weighted Tree Edit Distance Using Relaxation Labeling.- Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems.- A Complementary Pivoting Approach to Graph Matching.- Application of Genetic Algorithms to 3-D Shape Reconstruction in an Active Stereo Vision System.- Shapes, Curves, Surfaces, and Templates.- A Markov Process Using Curvature for Filtering Curve Images.- Geodesic Interpolating Splines.- Averaged Template Matching Equations.- A Continuous Shape Descriptor by Orientation Diffusion.- Multiple Contour Finding and Perceptual Grouping as a Set of Energy Minimizing Paths.- Shape Tracking Using Centroid-Based Methods.- Optical Flow and Image Registration: A New Local Rigidity Approach for Global Minimization.- Spherical Object Reconstruction Using Star-Shaped Simplex Meshes.- Gabor Feature Space Diffusion via the Minimal Weighted Area Method.- 3D Flux Maximizing Flows.

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