MADE: A Composite Visual-Based 3D Shape Descriptor
Biao Leng, Liqun Li, Zheng Qin
MIRAGE 2007: Computer Vision/Computer Graphics Collaboration Techniques, March 2007, pp. 93--104.
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.
Article URL: http://dx.doi.org/10.1007/978-3-540-71457-6_9
BibTeX format:
@incollection{Leng:2007:MAC,
  author = {Biao Leng and Liqun Li and Zheng Qin},
  title = {MADE: A Composite Visual-Based 3D Shape Descriptor},
  booktitle = {MIRAGE 2007: Computer Vision/Computer Graphics Collaboration Techniques},
  pages = {93--104},
  month = mar,
  year = {2007},
}
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