Energy Minimization Methods in Computer Vision and Pattern Recognition
Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings (Lecture Notes in Computer Science)
1 edition
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Author
Contributions
- Edwin R. Hancock (Editor) - Contributor
- Marcello Pelillo (Editor) - Contributor
Publication
1999-08-13 - Springer
Language
English
Word Count
82,750 words, Guess
Page Count
331 pages
Physical Format
Paperback
Identifiers
- Open LibraryOL9618600M
- ISBN-139783540662945
- ISBN-103540662944
- OCLC Control Number317790306
- OCLC Control Number41944748
and 3 more
- Internet Archiveenergyminimizati0000emmc_x9y9
- Library of Congress Control Number99040621
- Goodreads6144270
Classifications
- LCCTA1634 .E53 1999
Description
Energy Minimization Methods in Computer Vision and Pattern Recognition: Second International Workshop, EMMCVPR’99 York, UK, July 26–29, 1999 Proceedings<br />Author: Edwin R. Hancock, Marcello Pelillo<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-66294-5<br /> DOI: 10.1007/3-540-48432-9<br /><br />Table of Contents:<p></p><ul><li>A Hamiltonian Approach to the Eikonal Equation </li><li>Topographic Surface Structure from 2D Images Using Shape-from-Shading </li><li>Harmonic Shape Images: A Representation for 3D Free-Form Surfaces Based on Energy Minimization </li><li>Deformation Energy for Size Functions </li><li>On Fitting Mixture Models </li><li>Bayesian Models for Finding and Grouping Junctions </li><li>Semi-iterative Inferences with Hierarchical Energy-Based Models for Image Analysis </li><li>Metropolis vs Kawasaki Dynamic for Image Segmentation Based on Gibbs Models </li><li>Hyperparameter Estimation for Satellite Image Restoration by a MCMCML Method </li><li>Auxiliary Variables for Markov Random Fields with Higher Order Interactions </li><li>Unsupervised Multispectral Image Segmentation Using Generalized Gaussian Noise Model </li><li>Adaptive Bayesian Contour Estimation: A Vector Space Representation Approach </li><li>Adaptive Pixel-Based Data Fusion for Boundary Detection </li><li>Bayesian A* Tree Search with Expected O(N) Convergence Rates for Road Tracking </li><li>A New Algorithm for Energy Minimization with Discontinuities </li><li>Convergence of a Hill Climbing Genetic Algorithm for Graph Matching </li><li>A New Distance Measure for Non-rigid Image Matching </li><li>Continuous-Time Relaxation Labeling Processes </li><li>Realistic Animation Using Extended Adaptive Mesh for Model Based Coding </li><li>Maximum Likelihood Inference of 3D Structure from Image Sequences</li></ul>
First Sentence
Variational principles emerged naturally from considerations of energy minimization in mechanics [11].
Subjects
Topics
Other Editions
- Energy Minimization Methods in Computer Vision and Pattern Recognition: Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings (Lecture Notes in Computer Science)
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