MADE: a composite visual-based 3D shape descriptor

Authors:
Biao Leng;Liqun Li;Zheng Qin
Affiliations:
Department of Computer Science & Technology, Tsinghua University, Beijing, China and School of Software, Tsinghua University, Beijing, China;Department of Computer Science & Technology, Tsinghua University, Beijing, China and School of Software, Tsinghua University, Beijing, China;Department of Computer Science & Technology, Tsinghua University, Beijing, China and School of Software, Tsinghua University, Beijing, China
Venue:
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Year:
2007

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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.