Energy Minimization Methods in Computer Vision and Pattern Recognition: Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings

Energy Minimization Methods in Computer Vision and Pattern Recognition: Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings

Energy Minimization Methods in Computer Vision and Pattern Recognition: Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings

Energy Minimization Methods in Computer Vision and Pattern Recognition: Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings

Paperback(1999)

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Overview

This book constitutes the refereed proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'99, held in York, UK in July 1999.
The book presents 11 revised full papers together with 11 papers presented at the meeting as posters. Those papers were selected from a total of 33 submissions. The book is divided in sections on shape, minimum description length, Markov random fields, contours, search and consistent labeling, tracking and video, and biomedical applications.


Product Details

ISBN-13: 9783540662945
Publisher: Springer Berlin Heidelberg
Publication date: 08/13/1999
Series: Lecture Notes in Computer Science , #1654
Edition description: 1999
Pages: 338
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Shape.- A Hamiltonian Approach to the Eikonal Equation.- Topographic Surface Structure from 2D Images Using Shape-from-Shading.- Harmonic Shape Images: A Representation for 3D Free-Form Surfaces Based on Energy Minimization.- Deformation Energy for Size Functions.- Minimum Description Length.- On Fitting Mixture Models.- Bayesian Models for Finding and Grouping Junctions.- Markov Random Fields.- Semi-iterative Inferences with Hierarchical Energy-Based Models for Image Analysis.- Metropolis vs Kawasaki Dynamic for Image Segmentation Based on Gibbs Models.- Hyperparameter Estimation for Satellite Image Restoration by a MCMCML Method.- Auxiliary Variables for Markov Random Fields with Higher Order Interactions.- Unsupervised Multispectral Image Segmentation Using Generalized Gaussian Noise Model.- Contours.- Adaptive Bayesian Contour Estimation: A Vector Space Representation Approach.- Adaptive Pixel-Based Data Fusion for Boundary Detection.- Search and Consistent Labeling.- Bayesian A* Tree Search with Expected O(N) Convergence Rates for Road Tracking.- A New Algorithm for Energy Minimization with Discontinuities.- Convergence of a Hill Climbing Genetic Algorithm for Graph Matching.- A New Distance Measure for Non-rigid Image Matching.- Continuous-Time Relaxation Labeling Processes.- Tracking and Video.- Realistic Animation Using Extended Adaptive Mesh for Model Based Coding.- Maximum Likelihood Inference of 3D Structure from Image Sequences.- Biomedical Applications.- Magnetic Resonance Imaging Based Correction and Reconstruction of Positron Emission Tomography Images.- Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm4.
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