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MADE: A Composite Visual-Based 3D Shape Descriptor

  • Conference paper
Computer Vision/Computer Graphics Collaboration Techniques (MIRAGE 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4418))

Abstract

Due to the widely application of 3D models, the techniques of content-based 3D shape retrieval become necessary. In this paper, a modified Principal Component Analysis (PCA) method for model normalization is introduced at first, and each model is projected in 6 different viewpoints. Secondly, a new adjacent angle distance Fouriers (AADF) descriptor is presented, which captures more precise contour feature of black-white images. Finally, based on modified PCA method, a novel composite 3D shape descriptor MADE is proposed by concatenating AADF, Tchebichef and D-buffer descriptors. Experimental results on the criterion of 3D model database PSB show that the proposed descriptor MADE has gained the best retrieval effectiveness compared with three single descriptors and two composite descriptors LFD and DESIRE.

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Authors and Affiliations

  1. Department of Computer Science & Technology, Tsinghua University, 100084, Beijing, China, School of Software, Tsinghua University, 100084, Beijing, China

    Biao Leng, Liqun Li & Zheng Qin

Authors
  1. Biao Leng
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  2. Liqun Li
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  3. Zheng Qin
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André Gagalowicz Wilfried Philips

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© 2007 Springer Berlin Heidelberg

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Leng, B., Li, L., Qin, Z. (2007). MADE: A Composite Visual-Based 3D Shape Descriptor. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_9

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  • DOI: https://doi.org/10.1007/978-3-540-71457-6_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71456-9

  • Online ISBN: 978-3-540-71457-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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