Energy Minimization Methods in Computer Vision and Pattern Recognition

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

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.

• Computer-Vision
• Deformierbare Modelle
• Energieminimierung
• computer vision
• deformable models
• energy minimization
• neural networks
• pattern recognition
• algorithm analysis and problem complexity

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