Energy Minimization Methods in Computer Vision and Pattern Recognition

Unsupervised Learning and Matching.- Stochastic Search for Optimal Linear Representations of Images on Spaces with Orthogonality Constraints.- Local PCA for Strip Line Detection and Thinning.- Curve Matching Using the Fast Marching Method.- EM Algorithm for Clustering an Ensemble of Graphs with Comb Matching.- Information Force Clustering Using Directed Trees.- Watershed-Based Unsupervised Clustering.- Probabilistic Modelling.- Active Sampling Strategies for Multihypothesis Testing.- Likelihood Based Hierarchical Clustering and Network Topology Identification.- Learning Mixtures of Tree-Unions by Minimizing Description Length.- Image Registration and Segmentation by Maximizing the Jensen-Rényi Divergence.- Asymptotic Characterization of Log-Likelihood Maximization Based Algorithms and Applications.- Maximum Entropy Models for Skin Detection.- Hierarchical Annealing for Random Image Synthesis.- On Solutions to Multivariate Maximum ?-Entropy Problems.- Segmentation and Grouping.- Semi-supervised Image Segmentation by Parametric Distributional Clustering.- Path Variation and Image Segmentation.- A Fast Snake Segmentation Method Applied to Histopathological Sections.- A Compositionality Architecture for Perceptual Feature Grouping.- Using Prior Shape and Points in Medical Image Segmentation.- Separating a Texture from an Arbitrary Background Using Pairwise Grey Level Cooccurrences.- Shape Modelling.- Surface Recovery from 3D Point Data Using a Combined Parametric and Geometric Flow Approach.- Geometric Analysis of Continuous, Planar Shapes.- Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling.- Definition of a Signal-to-Noise Ratio for Object Segmentation Using Polygonal MDL-Based Statistical Snakes.- Restoration and Reconstruction.- Minimization of Cost-Functions with Non-smooth Data-Fidelity Terms to Clean Impulsive Noise.- A Fast GEM Algorithm for Bayesian Wavelet-Based Image Restoration Using a Class of Heavy-Tailed Priors.- Diffusion