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Computer Vision and Machine Learning with RGB-D Sensors pp 137–155Cite as

Matching of 3D Objects Based on 3D Curves

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Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

In this chapter, we introduce a novel approach to 3D object retrieval capable to match query objects generated by a user with those captured by a depth device (RGB-D). Our processing pipeline consists of several steps. In the preprocessing step, we first detect edges in the depth image and merge them to 2D object curves which allows a back-projection to 3D space. Then, we estimate a local coordinate system for these 3D curves. In the next step, distinctive feature points are localised and shortest paths between these points are determined. Subsequently, the shortest paths are represented by robust descriptors invariant to rotation, scaling, and translation. Finally, all the information collected to describe the object is used for matching. The matching process is transformed to the problem of Maximum Weight Subgraph search. Excellent retrieval results achieved in a comprehensive setup of challenging experiments show the benefits of our method comparing to the state-of-the-art.

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Acknowledgments

We would like to thank the German Research Foundation for financing the research work of Christian Feinen and Joanna Czajkowska within the Research Training Group 1564 “Imaging New Modalities”: http://www.grk1564.uni-siegen.de/en.

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Authors and Affiliations

  1. Pattern Recognition Group, University of Siegen, 57076, Siegen, Germany

    Christian Feinen, Joanna Czajkowska & Marcin Grzegorzek

  2. Department of Computer and Information Sciences, Temple University, Philadelphia, PA, 19122, USA

    Longin Jan Latecki

Authors
  1. Christian Feinen
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  2. Joanna Czajkowska
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  3. Marcin Grzegorzek
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  4. Longin Jan Latecki
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Corresponding author

Correspondence to Marcin Grzegorzek .

Editor information

Editors and Affiliations

  1. University of Sheffield, United Kingdom

    Ling Shao

  2. Civolution Technology, Eindhoven, The Netherlands

    Jungong Han

  3. Microsoft Research, Cambridge, United Kingdom

    Pushmeet Kohli

  4. Microsoft Research, Redmond, Washington, USA

    Zhengyou Zhang

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© 2014 Springer International Publishing Switzerland

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Feinen, C., Czajkowska, J., Grzegorzek, M., Latecki, L.J. (2014). Matching of 3D Objects Based on 3D Curves. In: Shao, L., Han, J., Kohli, P., Zhang, Z. (eds) Computer Vision and Machine Learning with RGB-D Sensors. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-08651-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-08651-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08650-7

  • Online ISBN: 978-3-319-08651-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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