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Multiple path exploration for graph matching

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Abstract

The graph matching problem is a hot topic in machine vision. Although a myriad of matching algorithms have been proposed during decades of investigation, it is still a challenging issue because of the combinatorial nature. As one of the outstanding graph matching algorithms, the graduated nonconvexity and concavity procedure follows the path following algorithm. The main drawback of this approach lies that there may exist singular points which violate the smoothness of the solution path and thus harm the accuracy of matching. Addressing this problem, we develop a novel algorithm to bypass this pitfall to improve the matching accuracy. We design an effective method of singular point discovering by checking the smoothness of the path and subsequently explore multiple smooth curves at detected points for better matching results. For evaluation, we make comparisons between our approach and several outstanding matching algorithms on three popular benchmarks, and the results reveal the advantage of our approach.

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Acknowledgements

This work is supported by the Fundamental Research Funds for the Central Universities, National Natural Science Foundation of China (Nos. 61472028, 61673048 and 61272352), Beijing Natural Science Foundation (Nos. 4162048 and 4163075) and Beijing Higher Education Young Elite Teacher Project (YETP0547).

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Correspondence to Tao Wang.

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Chen, R., Lang, C. & Wang, T. Multiple path exploration for graph matching. Machine Vision and Applications 28, 695–703 (2017). https://doi.org/10.1007/s00138-017-0847-1

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Keywords

  • Graph matching
  • GNCCP
  • Path following
  • Singular point
  • Multiple smooth curves