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Structural, Syntactic, and Statistical Pattern Recognition

Joint IAPR International Workshop, SSPR & SPR 2012, Hiroshima, Japan, November 7-9, 2012, Proceedings

  • Conference proceedings
  • © 2012

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Editors:
  1. Georgy Gimel’farb

    1. Department of Computer Science, University of Auckland, Auckland, New Zealand

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  2. Edwin Hancock

    1. Department of Computer Science, University of York, York, UK

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  3. Atsushi Imiya

    1. Institute of Media and Information Technology, Chiba University, Inage-ku, Japan

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  4. Arjan Kuijper

    1. Technische Universität/Fraunhofer IGD, Darmstadt, Germany

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  5. Mineichi Kudo

    1. Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan

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  6. Shinichiro Omachi

    1. Graduate School of Engineering, Tohoku University, Sendai, Japan

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  7. Terry Windeatt

    1. Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK

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  8. Keiji Yamada

    1. C&C Innovation Research Laboratories, NEC Corporation, Ikoma-Shi, Japan

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7626)

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

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Table of contents (82 papers)

  1. Front Matter

    Download chapter PDF

  2. Pierre Devijver Award Lecture

    1. Estimation, Learning, and Adaptation: Systems That Improve with Use

      • George Nagy
      Pages 1-10

  4. Structural, Syntactical, and Statistical Pattern Recognition

    1. Information Theoretic Prototype Selection for Unattributed Graphs

      • Lin Han, Luca Rossi, Andrea Torsello, Richard C. Wilson, Edwin R. Hancock
      Pages 33-41

    2. Graph Kernels: Crossing Information from Different Patterns Using Graph Edit Distance

      • Benoit Gaüzère, Luc Brun, Didier Villemin
      Pages 42-50

    3. Mode Seeking Clustering by KNN and Mean Shift Evaluated

      • Robert P. W. Duin, Ana L. N. Fred, Marco Loog, Elżbieta Pękalska
      Pages 51-59

    4. Learning Sparse Kernel Classifiers in the Primal

      • Zhouyu Fu, Guojun Lu, Kai-Ming Ting, Dengsheng Zhang
      Pages 60-69

  5. Graph and Tree Methods

    1. Evolutionary Weighted Mean Based Framework for Generalized Median Computation with Application to Strings

      • Lucas Franek, Xiaoyi Jiang
      Pages 70-78

    2. Graph Complexity from the Jensen-Shannon Divergence

      • Lu Bai, Edwin R. Hancock
      Pages 79-88

    3. Complexity of Computing Distances between Geometric Trees

      • Aasa Feragen
      Pages 89-97

    4. Active Graph Matching Based on Pairwise Probabilities between Nodes

      • Xavier Cortés, Francesc Serratosa, Albert Solé-Ribalta
      Pages 98-106

    5. On the Relation between the Common Labelling and the Median Graph

      • Nicola Rebagliati, Albert Solé-Ribalta, Marcello Pelillo, Francesc Serratosa
      Pages 107-115

  6. Randomized Methods and Image Analysis

    1. A Hierarchical Image Segmentation Algorithm Based on an Observation Scale

      • Silvio Jamil F. Guimarães, Jean Cousty, Yukiko Kenmochi, Laurent Najman
      Pages 116-125

    2. A Discrete Scale Space Neighborhood for Robust Deep Structure Extraction

      • Martin Tschirsich, Arjan Kuijper
      Pages 126-134

    3. On the Correlation of Graph Edit Distance and L 1 Distance in the Attribute Statistics Embedding Space

      • Jaume Gibert, Ernest Valveny, Horst Bunke, Alicia Fornés
      Pages 135-143

    4. Approximate Axial Symmetries from Continuous Time Quantum Walks

      • Luca Rossi, Andrea Torsello, Edwin R. Hancock
      Pages 144-152

    5. A Clustering-Based Ensemble Technique for Shape Decomposition

      • Sergej Lewin, Xiaoyi Jiang, Achim Clausing
      Pages 153-161

  7. Kernel Methods in Structural and Syntactical Pattern Recognition

    1. Laplacian Eigenimages in Discrete Scale Space

      • Martin Tschirsich, Arjan Kuijper
      Pages 162-170

    2. A Relational Kernel-Based Framework for Hierarchical Image Understanding

      • Laura Antanas, Paolo Frasconi, Fabrizio Costa, Tinne Tuytelaars, Luc De Raedt
      Pages 171-180
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  1. Structural, Syntactic, and Statistical Pattern Recognition

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About this book

This volume constitutes the refereed proceedings of the Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012), held in Hiroshima, Japan, in November 2012 as a satellite event of the 21st International Conference on Pattern Recognition, ICPR 2012. The 80 revised full papers presented together with 1 invited paper and the Pierre Devijver award lecture were carefully reviewed and selected from more than 120 initial submissions. The papers are organized in topical sections on structural, syntactical, and statistical pattern recognition, graph and tree methods, randomized methods and image analysis, kernel methods in structural and syntactical pattern recognition, applications of structural and syntactical pattern recognition, clustering, learning, kernel methods in statistical pattern recognition, kernel methods in statistical pattern recognition, as well as applications of structural, syntactical, and statistical methods.

Editors and Affiliations

  • Department of Computer Science, University of Auckland, Auckland, New Zealand

    Georgy Gimel’farb

  • Department of Computer Science, University of York, York, UK

    Edwin Hancock

  • Institute of Media and Information Technology, Chiba University, Inage-ku, Japan

    Atsushi Imiya

  • Technische Universität/Fraunhofer IGD, Darmstadt, Germany

    Arjan Kuijper

  • Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan

    Mineichi Kudo

  • Graduate School of Engineering, Tohoku University, Sendai, Japan

    Shinichiro Omachi

  • Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK

    Terry Windeatt

  • C&C Innovation Research Laboratories, NEC Corporation, Ikoma-Shi, Japan

    Keiji Yamada

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