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Energy Minimization Methods in Computer Vision and Pattern Recognition

International Workshop EMMCVPR'97, Venice, Italy, May 21-23, 1997, Proceedings

  • Conference proceedings
  • © 1997

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Editors:
  1. Marcello Pelillo
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  2. Edwin R. Hancock
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1223)

Included in the following conference series:

Conference proceedings info: EMMCVPR 1997.

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About this book

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 (34 papers)

  1. Front Matter

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  2. Reliable computation and related games

    • Douglas A. Miller, Steven W. Zucker
    Pages 1-18

  3. Characterizing the distribution of completion shapes with corners using a mixture of random processes

    • K. K. Thornber, L. R. Williams
    Pages 19-34

  4. Adaptive parametrically deformable contours

    • Mário A. T. Figueiredo, José M. N. Leitão, Anil K. Jain
    Pages 35-50

  5. Kona: A multi-junction detector using minimum description length principle

    • Laxmi Parida, Davi Geiger, Robert Hummel
    Pages 51-65

  6. Restoration of SAR images using recovery of discontinuities and non-linear optimization

    • Florence Tupin, Marc Sigelle, Ammar Chkeif, Jean-Pierre Véran
    Pages 67-82

  7. Geometrically deformable templates for shape-based segmentation and tracking in cardiac MR images

    • Daniel Rueckert, Peter Burger
    Pages 83-98

  8. Image segmentation via energy minimization on partitions with connected components

    • Jia-Ping Wang
    Pages 99-116

  9. Restoration of severely blurred high range images using stochastic and deterministic relaxation algorithms in compound gauss Markov random fields

    • Rafael Molina, Aggelos K. Katsaggelos, Javier Mateos, Aurora Hermoso
    Pages 117-132

  10. Maximum likelihood estimation of Markov Random Field parameters using Markov Chain Monte Carlo algorithms

    • Xavier Descombes, Robin Morris, Josiane Zerubia, Marc Berthod
    Pages 133-148

  11. Noniterative manipulation of discrete energy-based models for image analysis

    • Patrick Pérez, Jean-Marc Laferté
    Pages 149-164

  12. Unsupervised image segmentation using Markov Random Field models

    • S. A. Barker, P. J. W. Rayner
    Pages 165-178

  13. Adaptive anisotropic parameter estimation in the weak membrane model

    • Toshiro Kubota, Terry Huntsberger
    Pages 179-194

  14. Twenty questions, focus of attention, and A*: A theoretical comparison of optimization strategies

    • A. L. Yuille, J. Coughlan
    Pages 195-212

  15. Deterministic annealing for unsupervised texture segmentation

    • Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    Pages 213-228

  16. Self annealing: Unifying deterministic annealing and relaxation labeling

    • Anand Rangarajan
    Pages 229-244

  17. Multidimensional scaling by deterministic annealing

    • Hansjörg Klock, Joachim M. Buhmann
    Pages 245-260

  18. Deterministic search strategies for relational graph matching

    • Mark L. Williams, Richard C. Wilson, Edwin R. Hancock
    Pages 261-275

  19. Object localization using color, texture and shape

    • Yu Zhong, Anil K. Jain
    Pages 277-294

  20. Visual deconstruction: Recognizing articulated objects

    • Tyng-Luh Liu, Davi Geiger
    Pages 295-309
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