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Energy Minimization Methods in Computer Vision and Pattern Recognition Marcello Pelillo

Energy Minimization Methods in Computer Vision and Pattern Recognition By Marcello Pelillo

Energy Minimization Methods in Computer Vision and Pattern Recognition by Marcello Pelillo

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Summary

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.

Energy Minimization Methods in Computer Vision and Pattern Recognition Summary

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

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.

Table of Contents

Reliable computation and related games.- Characterizing the distribution of completion shapes with corners using a mixture of random processes.- Adaptive parametrically deformable contours.- Kona: A multi-junction detector using minimum description length principle.- Restoration of SAR images using recovery of discontinuities and non-linear optimization.- Geometrically deformable templates for shape-based segmentation and tracking in cardiac MR images.- Image segmentation via energy minimization on partitions with connected components.- Restoration of severely blurred high range images using stochastic and deterministic relaxation algorithms in compound gauss Markov random fields.- Maximum likelihood estimation of Markov Random Field parameters using Markov Chain Monte Carlo algorithms.- Noniterative manipulation of discrete energy-based models for image analysis.- Unsupervised image segmentation using Markov Random Field models.- Adaptive anisotropic parameter estimation in the weak membrane model.- Twenty questions, focus of attention, and A*: A theoretical comparison of optimization strategies.- Deterministic annealing for unsupervised texture segmentation.- Self annealing: Unifying deterministic annealing and relaxation labeling.- Multidimensional scaling by deterministic annealing.- Deterministic search strategies for relational graph matching.- Object localization using color, texture and shape.- Visual deconstruction: Recognizing articulated objects.- Optimization problems in statistical object recognition.- Object recognition using stochastic optimization.- Genetic algorithms for ambiguous labelling problems.- Toward global solution to MAP image estimation: Using Common structure of local solutions.- Figure-ground separation: A case study in energy minimization via evolutionary computing.- Probabilistic relaxation: Potential, relationships and open problems.- A region-level motion-based graph representation and labeling for tracking a spatial image partition.- An expectation-maximisation approach to graph matching.- An energy minimization method for matching and comparing structured object representations.- Consistent modeling of terrain and drainage using deformable models.- Integration of confidence information by Markov Random Fields for reconstruction of underwater 3D acoustic images.- Unsupervised segmentation applied on sonar images.- SAR image registration and segmentation using an estimated DEM.- Deformable templates for tracking and analysis of intravascular ultrasound sequences.- Motion correspondence through energy minimization.

Additional information

GOR012512954
9783540629092
3540629092
Energy Minimization Methods in Computer Vision and Pattern Recognition: International Workshop EMMCVPR'97, Venice, Italy, May 21-23, 1997, Proceedings by Marcello Pelillo
Marcello Pelillo
Lecture Notes in Computer Science
Used - Very Good
Paperback
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
19970429
556
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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