Energy Minimization Methods in Computer Vision and Pattern Recognition
Subtitle: Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings (Lecture Notes in Computer Science)
Contributors: Edwin R. Hancock (Editor); Marcello Pelillo (Editor)
Edition: 1 edition
Publisher: Springer
Published: August 13, 1999
Language: eng
Format: Paperback
Number of pages: 331
ISBN-13: 9783540662945
Subjects: Computer Programming; Computer Vision; Image processing; Pattern Recognition; Pattern recognition systems; Evolutionary computation; Computers; Computers - General Information; Science/Mathematics; Neural networks (Computer science); General; Biomathematics; Computers / Computer Vision; Energy Minimization; Markov Random Fields; Data Processing - General; Congresses; Neural networks (Computer scie
First sentence: Variational principles emerged naturally from considerations of energy minimization in mechanics [11].
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>