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Graph-Based Representations in Pattern Recognition

7th IAPR-TC-15 International Workshop, GbRPR 2009, Venice, Italy, May 26-28, 2009. Proceedings

  • Conference proceedings
  • © 2009

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Editors:
  1. Andrea Torsello

    1. “Ca’ Foscari” University of Venice, Italy

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  2. Francisco Escolano

    1. Department of Computer Science and Artificial Intelligence, Alicante University, Alicante, Spain

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  3. Luc Brun

    1. GREYC CNRS UMR 6072, Image Team, Université de Caen Basse-Normandie, Caen Cedex, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5534)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

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Conference proceedings info: GbRPR 2009.

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About this book

This book constitutes the refereed proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2009, held in Venice, Italy in May 2009.

The 37 revised full papers presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on graph-based representation and recognition, graph matching, graph clustering and classification, pyramids, combinatorial maps, and homologies, as well as graph-based segmentation.

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Table of contents (37 papers)

  1. Front Matter

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  2. Graph-Based Representation and Recognition

    1. Matching Hierarchies of Deformable Shapes

      • Nadia Payet, Sinisa Todorovic
      Pages 1-10

    2. Edition within a Graph Kernel Framework for Shape Recognition

      • François-Xavier Dupé, Luc Brun
      Pages 11-20

    3. Coarse-to-Fine Matching of Shapes Using Disconnected Skeletons by Learning Class-Specific Boundary Deformations

      • Aykut Erdem, Sibel Tari
      Pages 21-30

    4. An Optimisation-Based Approach to Mesh Smoothing: Reformulation and Extensions

      • Yskandar Hamam, Michel Couprie
      Pages 31-41

    5. Graph-Based Representation of Symbolic Musical Data

      • Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer
      Pages 42-51

    6. Graph-Based Analysis of Nasopharyngeal Carcinoma with Bayesian Network Learning Methods

      • Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex, Joël Favrel
      Pages 52-61

    7. Computing and Visualizing a Graph-Based Decomposition for Non-manifold Shapes

      • Leila De Floriani, Daniele Panozzo, Annie Hui
      Pages 62-71

    8. A Graph Based Data Model for Graphics Interpretation

      • Endre Katona
      Pages 72-81

    9. Tracking Objects beyond Rigid Motion

      • Nicole Artner, Adrian Ion, Walter G. Kropatsch
      Pages 82-91

    10. Graph-Based Registration of Partial Images of City Maps Using Geometric Hashing

      • Steffen Wachenfeld, Klaus Broelemann, Xiaoyi Jiang, Antonio Krüger
      Pages 92-101

  3. Graph Matching

    1. A Polynomial Algorithm for Submap Isomorphism

      • Guillaume Damiand, Colin de la Higuera, Jean-Christophe Janodet, Émilie Samuel, Christine Solnon
      Pages 102-112

    2. A Recursive Embedding Approach to Median Graph Computation

      • M. Ferrer, D. Karatzas, E. Valveny, H. Bunke
      Pages 113-123

    3. Efficient Suboptimal Graph Isomorphism

      • Kaspar Riesen, Stefan Fankhauser, Horst Bunke, Peter Dickinson
      Pages 124-133

    4. Homeomorphic Alignment of Edge-Weighted Trees

      • Benjamin Raynal, Michel Couprie, Venceslas Biri
      Pages 134-143

    5. Inexact Matching of Large and Sparse Graphs Using Laplacian Eigenvectors

      • David Knossow, Avinash Sharma, Diana Mateus, Radu Horaud
      Pages 144-153

    6. Graph Matching Based on Node Signatures

      • Salim Jouili, Salvatore Tabbone
      Pages 154-163

    7. A Structural and Semantic Probabilistic Model for Matching and Representing a Set of Graphs

      • Albert Solé-Ribalta, Francesc Serratosa
      Pages 164-173

    8. Arc-Consistency Checking with Bilevel Constraints: An Optimization

      • Aline Deruyver, Yann Hodé
      Pages 174-183

  4. Graph Clustering and Classification

    1. Pairwise Similarity Propagation Based Graph Clustering for Scalable Object Indexing and Retrieval

      • Shengping Xia, Edwin R. Hancock
      Pages 184-194
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Other volumes

  1. Graph-Based Representations in Pattern Recognition

Editors and Affiliations

  • “Ca’ Foscari” University of Venice, Italy

    Andrea Torsello

  • Department of Computer Science and Artificial Intelligence, Alicante University, Alicante, Spain

    Francisco Escolano

  • GREYC CNRS UMR 6072, Image Team, Université de Caen Basse-Normandie, Caen Cedex, France

    Luc Brun

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