Energy Minimization Methods in Computer Vision and Pattern Recognition

4th International Workshop, EMMCVPR 2003, Lisbon, Portugal, July 7-9, 2003. Proceedings

Editors:

ISBN: 978-3-540-40498-9 (Print) 978-3-540-45063-4 (Online)

Table of contents (33 chapters)

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  1. Front Matter

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  2. Unsupervised Learning and Matching

    1. Front Matter

      Pages 1-1

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      Pages 3-20

      Stochastic Search for Optimal Linear Representations of Images on Spaces with Orthogonality Constraints

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      Pages 21-34

      Local PCA for Strip Line Detection and Thinning

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      Pages 35-51

      Curve Matching Using the Fast Marching Method

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      Pages 52-67

      EM Algorithm for Clustering an Ensemble of Graphs with Comb Matching

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      Pages 68-82

      Information Force Clustering Using Directed Trees

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      Pages 83-94

      Watershed-Based Unsupervised Clustering

  3. Probabilistic Modelling

    1. Front Matter

      Pages 95-95

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      Pages 97-112

      Active Sampling Strategies for Multihypothesis Testing

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      Pages 113-129

      Likelihood Based Hierarchical Clustering and Network Topology Identification

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      Pages 130-146

      Learning Mixtures of Tree-Unions by Minimizing Description Length

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      Pages 147-163

      Image Registration and Segmentation by Maximizing the Jensen-Rényi Divergence

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      Pages 164-179

      Asymptotic Characterization of Log-Likelihood Maximization Based Algorithms and Applications

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      Pages 180-193

      Maximum Entropy Models for Skin Detection

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      Pages 194-210

      Hierarchical Annealing for Random Image Synthesis

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      Pages 211-226

      On Solutions to Multivariate Maximum α-Entropy Problems

  4. Segmentation and Grouping

    1. Front Matter

      Pages 227-227

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      Pages 229-245

      Semi-supervised Image Segmentation by Parametric Distributional Clustering

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      Pages 246-260

      Path Variation and Image Segmentation

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      Pages 261-274

      A Fast Snake Segmentation Method Applied to Histopathological Sections

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      Pages 275-290

      A Compositionality Architecture for Perceptual Feature Grouping

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      Pages 291-305

      Using Prior Shape and Points in Medical Image Segmentation

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      Book Chapter

      Pages 306-322

      Separating a Texture from an Arbitrary Background Using Pairwise Grey Level Cooccurrences

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