Energy Minimization Methods in Computer Vision and Pattern Recognition: International Workshop EMMCVPR'97 Venice, Italy, May 21–23, 1997 Proceedings

✍ Scribed by Douglas A. Miller, Steven W. Zucker (auth.), Marcello Pelillo, Edwin R. Hancock

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 1997
• Tongue: English
• Leaves: 558
• Category: Library

✦ Synopsis

This book constitutes the refereed proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'97, held in Venice, Italy, in May 1997.
The book presents 29 revised full papers selected from a total of 62 submissions. Also included are four full invited papers and a keynote paper by leading researchers. The volume is organized in sections on contours and deformable models, Markov random fields, deterministic methods, object recognition, evolutionary search, structural models, and applications. The volume is the first comprehensive documentation of the application of energy minimization techniques in the areas of compiler vision and pattern recognition.
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✦ Table of Contents

Energy Minimization Methods in Computer Vision and Pattern Recognition 1997
Cover
Copyrights
Preface
Contents
2 Reliable computation and related games
3 Characterizing the distribution of completion shapes with corners using a mixture of random processes
4 Adaptive parametrically deformable contours
5 Kona A multi-junction detector using minimum description length principle
6 Restoration of SAR images using recovery of discontinuities and non-linear optimization
7 Geometrically deformable templates for shape-based segmentation and tracking in cardiac MR images
8 Image segmentation via energy minimization on partitions with connected components
9 Restoration of severely blurred high range images using stochastic and deterministic relaxation algorithms in compound gauss Markov random fields
10 Maximum likelihood estimation of Markov Random Field parameters using Markov Chain Monte Carlo algorithms
11 Noniterative manipulation of discrete energy-based models for image analysis
12 Unsupervised image segmentation using Markov Random Field models
13 Adaptive anisotropic parameter estimation in the weak membrane model
14 Twenty questions, focus of attention, and A A theoretical comparison of optimization strategies
15 Deterministic annealing for unsupervised texture segmentation
16 Self annealing Unifying deterministic annealing and relaxation labeling
17 Multidimensional scaling by deterministic annealing
18 Deterministic search strategies for relational graph matching
19 Object localization using color, texture and shape
20 Visual deconstruction Recognizing articulated objects
21 Optimization problems in statistical object recognition
22 Object recognition using stochastic optimization
23 Genetic algorithms for ambiguous labelling problems
24 Toward global solution to MAP image estimation Using Common structure of local solutions
25 Figure-ground separation A case study in energy minimization via evolutionary computing
26 Probabilistic relaxation Potential, relationships and open problems
27 A region-level motion-based graph representation and labeling for tracking a spatial image partition
28 An expectation-maximisation approach to graph matching
29 An energy minimization method for matching and comparing structured object representations
30 Consistent modeling of terrain and drainage using deformable models
31 Integration of confidence information by Markov Random Fields for reconstruction of underwater 3D acoustic images
32 Unsupervised segmentation applied on sonar images
33 SAR image registration and segmentation using an estimated DEM
34 Deformable templates for tracking and analysis of intravascular ultrasound sequences
35 Motion correspondence through energy minimization
Author Index

✦ Subjects

Pattern Recognition; Artificial Intelligence (incl. Robotics}