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European Conference on Computer Vision

ECCV 2020: Computer Vision – ECCV 2020 pp 251–267Cite as

Layered Neighborhood Expansion for Incremental Multiple Graph Matching

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12355))

Abstract

Graph matching has been a fundamental problem in computer vision and pattern recognition, for its practical flexibility as well as NP hardness challenge. Though the matching between two graphs and among multiple graphs have been intensively studied in literature, the online setting for incremental matching of a stream of graphs has been rarely considered. In this paper, we treat the graphs as graphs on a super-graph, and propose a novel breadth first search based method for expanding the neighborhood on the super-graph for a new coming graph, such that the matching with the new graph can be efficiently performed within the constructed neighborhood. Then depth first search is performed to update the overall pairwise matchings. Moreover, we show our approach can also be readily used in the batch mode setting, by adaptively determining the order of coming graph batch for matching, still under the neighborhood expansion based incremental matching framework. Experiments on both online and offline matching of graph collections show our approach’s state-of-the-art accuracy and efficiency.

Work was partly supported by National Key Research and Development Program of China 2018AAA0100704, NSFC (61972250, U19B2035), and SJTU Global Strategic Partnership Fund (2020 SJTU-CORNELL).

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Notes

  1. 1.

    We assume graphs are of equal size in this paper, which can be obtained by adding dummy nodes if needed as widely done in literature [6].

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Zixuan Chen, Zhihui Xie & Junchi Yan

  2. MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China

    Zixuan Chen, Zhihui Xie, Junchi Yan & Xiaokang Yang

  3. National Institute of Informatics, Chiyoda, Japan

    Yinqiang Zheng

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  1. Zixuan Chen
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  2. Zhihui Xie
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  3. Junchi Yan
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  4. Yinqiang Zheng
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  5. Xiaokang Yang
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Corresponding author

Correspondence to Junchi Yan .

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Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Andrea Vedaldi

  2. Graz University of Technology, Graz, Austria

    Horst Bischof

  3. University of Freiburg, Freiburg im Breisgau, Germany

    Thomas Brox

  4. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jan-Michael Frahm

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Chen, Z., Xie, Z., Yan, J., Zheng, Y., Yang, X. (2020). Layered Neighborhood Expansion for Incremental Multiple Graph Matching. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, JM. (eds) Computer Vision – ECCV 2020. ECCV 2020. Lecture Notes in Computer Science(), vol 12355. Springer, Cham. https://doi.org/10.1007/978-3-030-58607-2_15

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  • DOI: https://doi.org/10.1007/978-3-030-58607-2_15

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  • Print ISBN: 978-3-030-58606-5

  • Online ISBN: 978-3-030-58607-2

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