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Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR)

SSPR /SPR 2012: Structural, Syntactic, and Statistical Pattern Recognition pp 98–106Cite as

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  2. Structural, Syntactic, and Statistical Pattern Recognition
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Active Graph Matching Based on Pairwise Probabilities between Nodes

Active Graph Matching Based on Pairwise Probabilities between Nodes

  • Xavier Cortés24,
  • Francesc Serratosa24 &
  • Albert Solé-Ribalta24 
  • Conference paper
  • 2432 Accesses

  • 8 Citations

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

Abstract

We propose a method to perform active graph matching in which the active learner queries one of the nodes of the first graph and the oracle feedback is the corresponding node of the other graph. The method uses any graph matching algorithm that iteratively updates a probability matrix between nodes (Graduated Assignment, Expectation Maximisation or Probabilistic Relaxation). The oracle’s feedback is used to update the costs between nodes and arcs of both graphs. We present and validate four different active strategies based on the probability matrix between nodes. It is not needed to modify the code of the graph-matching algorithms, since our method simply needs to read the probability matrix and to update the costs between nodes and arcs. Practical validation shows that with few oracle’s feedbacks, the algorithm finds the labelling that the user considers optimal because imposing few labellings the other ones are corrected automatically.

Keywords

  • Machine Learning
  • Active Graph Matching
  • Interactive Graph Matching
  • Least Confident
  • Maximum Entropy
  • Expected Model Change

This research is supported by Consolider Ingenio 2010: project CSD2007-00018 & by the CICYT project DPI 2010-17112.

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Author information

Authors and Affiliations

  1. Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Spain

    Xavier Cortés, Francesc Serratosa & Albert Solé-Ribalta

Authors
  1. Xavier Cortés
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  2. Francesc Serratosa
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  3. Albert Solé-Ribalta
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Auckland, Private Bag 92019, 1142, Auckland, New Zealand

    Georgy Gimel’farb

  2. Department of Computer Science, University of York, Deramore Lane, YO10 5GH, York, UK

    Edwin Hancock

  3. Institute of Media and Information Technology, Chiba University, Yayoi-cho 1-33, 263-8522, Inage-ku, Chiba, Japan

    Atsushi Imiya

  4. Technische Universität/Fraunhofer IGD, Fraunhoferstraße 5, 64283, Darmstadt, Germany

    Arjan Kuijper

  5. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan

    Mineichi Kudo

  6. Graduate School of Engineering, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, 980-8579, Sendai, Miyagi, Japan

    Shinichiro Omachi

  7. Centre for Vision, Speech and Signal Processing, University of Surrey, GU2 7XH, Guildford, Surrey, UK

    Terry Windeatt

  8. C&C Innovation Research Laboratories, NEC Corporation, 8916-47 Takayama-cho, Ikoma-Shi, Nara, Japan

    Keiji Yamada

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© 2012 Springer-Verlag Berlin Heidelberg

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Cortés, X., Serratosa, F., Solé-Ribalta, A. (2012). Active Graph Matching Based on Pairwise Probabilities between Nodes. In: Gimel’farb, G., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2012. Lecture Notes in Computer Science, vol 7626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34166-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-34166-3_11

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