Energy Minimization Methods in Computer Vision and Pattern Recognition (eBook, PDF)

4th International Workshop, EMMCVPR 2003, Lisbon, Portugal, July 7-9, 2003, Proceedings
Redaktion: Rangarajan, Anand; Zerubia, Josiane; Figueiredo, Mário A. T.

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 4th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2003, held in Lisbon, Portugal in July 2003. The 33 revised full papers presented were carefully reviewed and selected from 66 submissions. The papers are organized in topical sections on unsupervised learning and matching, probabilistic modeling, segmentation and grouping, shape modeling, restoration and reconstruction, and graphs and graph-based methods.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 534
• Erscheinungstermin: 2. Oktober 2003
• Englisch
• ISBN-13: 9783540450634
• Artikelnr.: 53389423

Inhaltsangabe

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 Tensor MR Image Restoration.- A MAP Estimation Algorithm Using IIR Recursive Filters.- Estimation of Rank Deficient Matrices from Partial Observations: Two-Step Iterative Algorithms.- Contextual and Non-combinatorial Approach to Feature Extraction.- Graphs and Graph-Based Methods.- Generalizing the Motzkin-Straus Theorem to Edge-Weighted Graphs, with Applications to Image Segmentation.- Generalized Multi-camera Scene Reconstruction Using Graph Cuts.- Graph Matching Using Spectral Seriation.