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Joint Tree of Combinatorial Maps

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Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8643))

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Abstract

Combinatorial maps are widely used in the field of computer vision, including image segmentation, medical image analysis and mobile robotics. Many practical problems can be formulated as the combinatorial map matching problem. This paper addresses the problem of inexact matching between labeled combinatorial maps. We define Joint Tree of combinatorial maps, and prove it can be used to decide of map isomorphism. In this way, the map matching problem is relaxed to the Joint Tree matching problem, which can be solved in polynomial time. Our approach provides a novel way to explore the problem of combinatorial map matching.

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Acknowledgements

This work is supported by the National Nature Science Foundation of China (Nos. 61300071, 61272352, 61100142) and the Fundamental Research Funds for the Central Universities (No. 2012JBM040).

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Authors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China

    Tao Wang, Congyan Lang & Songhe Feng

Authors
  1. Tao Wang
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  2. Congyan Lang
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  3. Songhe Feng
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Corresponding author

Correspondence to Tao Wang .

Editor information

Editors and Affiliations

  1. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Chih Peng

  2. Google Research, Mountain View, California, USA

    Haixun Wang

  3. University of Melbourne, Melbourne, Victoria, Australia

    James Bailey

  4. National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  5. Japan Advanced Institute of Science and Technology, Nomi City, Japan

    Tu Bao Ho

  6. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  7. National Chengchi University, Taipei, Taiwan

    Arbee L.P. Chen

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© 2014 Springer International Publishing Switzerland

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Wang, T., Lang, C., Feng, S. (2014). Joint Tree of Combinatorial Maps. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_3

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  • DOI: https://doi.org/10.1007/978-3-319-13186-3_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13185-6

  • Online ISBN: 978-3-319-13186-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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