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Structural, Syntactic, and Statistical Pattern Recognition

Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings

  • Niels da Vitoria Lobo
  • Takis Kasparis
  • Fabio Roli
  • James T. Kwok
  • Michael Georgiopoulos
  • Georgios C. Anagnostopoulos
  • Marco Loog

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5342)

Table of contents

  1. Front Matter
  2. Invited Talks (Abstracts)

    1. Horst Bunke, Kaspar Riesen
      Pages 2-2
    2. Pedro Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matt Richardson, Parag Singla et al.
      Pages 3-3
  3. SSPR

    1. Graph-Based Methods (Special Session)

      1. David Emms, Richard C. Wilson, Edwin R. Hancock
        Pages 5-14
      2. Miquel Ferrer, Ernest Valveny, Francesc Serratosa, Horst Bunke
        Pages 15-24
      3. Dongjoe Shin, Tardi Tjahjadi
        Pages 25-34
      4. Wan-Jui Lee, Robert P. W. Duin
        Pages 35-44
      5. Nicolas Sidere, Pierre Heroux, Jean-Yves Ramel
        Pages 45-54
    2. Probabilistic and Stochastic Structural Models for PR

      1. Carlos Pérez-Sancho, David Rizo, José M. Iñesta
        Pages 55-64
      2. Franck Thollard, Baptiste Jeudy
        Pages 65-75
      3. Arnaud Zdziobeck, Franck Thollard
        Pages 76-85
      4. Amaury Habrard, José Manuel Iñesta, David Rizo, Marc Sebban
        Pages 86-96
      5. Daniel Heesch, Robby Tan, Maria Petrou
        Pages 97-106
    3. Image and Video Analysis

      1. Yunqian Ma, Petr Cisar
        Pages 107-116
      2. Alexander Shorin, Georgy Gimel’farb, Patrice Delmas, Jonh Morris
        Pages 127-136
      3. Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Gallo, Roberto Cipolla
        Pages 137-146
      4. Nicholas Shorter, Takis Kasparis
        Pages 147-156
    4. Shape Analysis

      1. James Sharpe, Edwin R. Hancock
        Pages 157-166
      2. Reinier H. van Leuken, Olga Symonova, Remco C. Veltkamp, Raffaele de Amicis
        Pages 167-176
      3. Boris Flach, Dmitrij Schlesinger
        Pages 177-186
      4. Andrea Albarelli, Marcello Pelillo, Sebastiano Viviani
        Pages 197-206
    5. Kernel Methods

      1. Hewayda ElGhawalby, Edwin R. Hancock
        Pages 207-216
      2. Bai Xiao, Richard C. Wilson, Edwin R. Hancock
        Pages 217-226
      3. François-Xavier Dupé, Luc Brun
        Pages 227-236
      4. Francisco Escolano, Edwin R. Hancock, Miguel A. Lozano
        Pages 237-246
      5. Heeyoul Choi, Brandon Paulson, Tracy Hammond
        Pages 247-256
    6. Pattern Recognition and Applications (Jointly with SPR)

      1. Peng Ren, Richard C. Wilson, Edwin R. Hancock
        Pages 257-266
      2. Indriyati Atmosukarto, Linda G. Shapiro
        Pages 267-276
      3. Huanzhang Fu, Alain Pujol, Emmanuel Dellandréa, Liming Chen
        Pages 277-286
  4. Poster Papers

    1. Graph-Based Methods

      1. Peng Ren, Richard C. Wilson, Edwin R. Hancock
        Pages 308-317
      2. Shengping Xia, Edwin R. Hancock
        Pages 318-328
      3. Bai Xiao, Yi-Zhe Song, Anupriya Balika, Peter M. Hall
        Pages 329-338
    2. Recognition and Classification

      1. Guillaume Née, Stéphanie Jehan-Besson, Luc Brun, Marinette Revenu
        Pages 350-360
      2. Helena Molina-Abril, Pedro Real
        Pages 361-371
      3. Simon Fothergill, Robert Harle, Sean Holden
        Pages 372-381
    3. Image and Video Analysis

    4. Applications

      1. Cristian Olivares-Rodríguez, Jose Oncina
        Pages 431-440
      2. Nicole M. Artner, Salvador B. López Mármol, Csaba Beleznai, Walter G. Kropatsch
        Pages 441-450

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 12th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2008 and the 7th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2008, held jointly in Orlando, FL, USA, in December 2008 as a satellite event of the 19th International Conference of Pattern Recognition, ICPR 2008.

The 56 revised full papers and 42 revised poster papers presented together with the abstracts of 4 invited papers were carefully reviewed and selected from 175 submissions. The papers are organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, computer vision and biometrics, pattern recognition and applications, pattern recognition, as well as feature selection and clustering.

Keywords

3D object classification audio content mining bayesian networks biometrics character recognition classification clustering document analysis face recognition fingerprint graph matching graph-based methods graphical pattern pattern recognition video analysis

Editors and affiliations

  • Niels da Vitoria Lobo
    • 1
  • Takis Kasparis
    • 2
  • Fabio Roli
    • 3
  • James T. Kwok
    • 4
  • Michael Georgiopoulos
    • 2
  • Georgios C. Anagnostopoulos
    • 5
  • Marco Loog
    • 6
  1. 1.University of Central Florida School of Electrical Engineering and Computer Science, OrlandoFloridaUSA
  2. 2.University of Central Florida OrlandoFloridaUSA
  3. 3.Department of Electrical and Electronic Engineering University of CagliariCagliariItaly
  4. 4.Department of Computer Science Hong KongUniversity of Science and TechnologyHong KongChina
  5. 5.Department of Electrical and Computer EngineeringMelbourne Florida Institute of TechnologyFloridaUSA
  6. 6.Delft University of Technology, Delft, The Netherlands and University of CopenhagenCopenhagenDenmark

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-89689-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-89688-3
  • Online ISBN 978-3-540-89689-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site