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Shape Matching Using Point Context and Contour Segments

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Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9006))

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Abstract

This paper proposes a novel method to generate robust contour partition points and applies them to produce point context and contour segment features for shape matching. The main idea is to match object shapes by matching contour partition points and contour segments. In contrast to typical shape context method, we do not consider the topological graph structure since our approach is only considering a small number of partition points rather than full contour points. The experimental results demonstrate that our method is able to produce correct results in the presence of articulations, stretching, and contour deformations. The most significant scientific contributions of this paper include (i) the introduction of a novel partition point extraction technique for point context and contour segments as well as (ii) a new fused similarity measure for object matching and recognition, and (iii) the impressive robustness of the method in an object retrieval scenario as well as in a real application for environmental microorganism recognition.

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Acknowledgement

Research activities leading to this work have been supported by the China Scholarship Council, the German Research Foundation (DFG) within the Research Training Group 1564. We greatly thank M.Sc Chen Li from the University of Siegen for providing us with the Environmental Microorganism image dataset for experiments. We are also very grateful to Dr. Kimiaki Shirahama from University of Siegen for his guiding on significant technologies.

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Authors and Affiliations

  1. Research Group for Pattern Recognition, Department ETI, University of Siegen, Hoelderlinstr. 3, 57076, Siegen, Germany

    Christian Feinen, Cong Yang, Oliver Tiebe & Marcin Grzegorzek

Authors
  1. Christian Feinen
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  2. Cong Yang
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  3. Oliver Tiebe
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  4. Marcin Grzegorzek
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Corresponding author

Correspondence to Marcin Grzegorzek .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Feinen, C., Yang, C., Tiebe, O., Grzegorzek, M. (2015). Shape Matching Using Point Context and Contour Segments. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9006. Springer, Cham. https://doi.org/10.1007/978-3-319-16817-3_7

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  • DOI: https://doi.org/10.1007/978-3-319-16817-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16816-6

  • Online ISBN: 978-3-319-16817-3

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