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Hyper-graph Matching with Bundled Feature

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Intelligence Science and Big Data Engineering (IScIDE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8261))

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Abstract

Hyper-graph matching algorithm describes the whole structure of object by high-order topology. Previous work has presented many methods to build and solve the problem model. This paper mainly focuses on feature description and result optimization. First, we combine several features in stable region of object as bundled feature, it can describe more relationship by hyper-graph model. Second, we properly extend previous work to build and solve the hyper-graph model. Finally, we optimize the matching result by iteration and modifying constraints, it improves the accuracy effectively. Comparative experiments verify the good performance of our algorithm, especially for non-rigid object matching.

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Author information

Authors and Affiliations

  1. Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China

    Deyuan Li & Yue Zhou

Authors
  1. Deyuan Li
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  2. Yue Zhou
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Editor information

Editors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology, Xueyuan Road No. 30, 100083, Beijing, China

    Changyin Sun

  2. Department of Psychology, Peking University, Yiheyuan Road No. 5, 100871, Beijing, China

    Fang Fang

  3. Department of Computer Science and Technology, Nanjing University, Xianlin Avenue No. 163, 210023, Nanjing, China

    Zhi-Hua Zhou

  4. School of Automation, Southeast University, Sipailou No. 2, 210096, Nanjing, China

    Wankou Yang

  5. Institute of Automation, Chinese Academy of Sciences, No. 95 East Zhongguancun Road, 100190, Beijing, China

    Zhi-Yong Liu

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© 2013 Springer-Verlag Berlin Heidelberg

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Li, D., Zhou, Y. (2013). Hyper-graph Matching with Bundled Feature. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_85

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  • DOI: https://doi.org/10.1007/978-3-642-42057-3_85

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42056-6

  • Online ISBN: 978-3-642-42057-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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