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Proceedings Paper

3D CAD model retrieval method based on hierarchical multi-features
Author(s): Ran An; Qingwen Wang
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Paper Abstract

The classical “Shape Distribution D2” algorithm takes the distance between two random points on a surface of CAD model as statistical features, and based on that it generates a feature vector to calculate the dissimilarity and achieve the retrieval goal. This algorithm has a simple principle, high computational efficiency and can get a better retrieval results for the simple shape models. Based on the analysis of D2 algorithm’s shape distribution curve, this paper enhances the algorithm’s descriptive ability for a model’s overall shape through the statistics of the angle between two random points’ normal vectors, especially for the distinctions between the model’s plane features and curved surface features; meanwhile, introduce the ratio that a line between two random points cut off by the model’s surface to enhance the algorithm’s descriptive ability for a model’s detailed features; finally, integrating the two shape describing methods with the original D2 algorithm, this paper proposes a new method based the hierarchical multi-features. Experimental results showed that this method has bigger improvements and could get a better retrieval results compared with the traditional 3D CAD model retrieval method.

Paper Details

Date Published: 9 December 2015
PDF: 9 pages
Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 98170B (9 December 2015); doi: 10.1117/12.2228423
Show Author Affiliations
Ran An, Beihang Univ. (China)
Qingwen Wang, Beihang Univ. (China)


Published in SPIE Proceedings Vol. 9817:
Seventh International Conference on Graphic and Image Processing (ICGIP 2015)
Yulin Wang; Xudong Jiang, Editor(s)

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