MADE: A Composite Visual-Based 3D Shape Descriptor

  • Biao Leng
  • Liqun Li
  • Zheng Qin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4418)


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.


Shape Descriptor Retrieval Performance Fourier Descriptor Good Retrieval Centroid Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Biao Leng
    • 1
  • Liqun Li
    • 1
  • Zheng Qin
    • 1
  1. 1.Department of Computer Science & Technology, Tsinghua University, 100084, Beijing, China, School of Software, Tsinghua University, 100084, BeijingChina

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