Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-540-69423-6_6
Title: A shape distribution for comparing 3D models
Authors: Monteverde, L.C.
Ruiz, C.R.
HUANG ZHIYONG 
Issue Date: 2007
Citation: Monteverde, L.C., Ruiz, C.R., HUANG ZHIYONG (2007). A shape distribution for comparing 3D models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4351 LNCS (PART 1) : 54-63. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-540-69423-6_6
Abstract: This study developed a new shape-based 3D model descriptor based on the D2 shape descriptor developed by Osada, et al of Princeton University. Shape descriptors can be used to measure dissimilarity between two 3D models. In this work, we advance it by proposing a novel descriptor D2a. In our method, N pairs of faces are randomly chosen from a 3D model, with probability proportional to the area of the face. The ratio of the smaller area over the larger area is computed and its frequency stored, generating a frequency distribution of N ratios which is stored as the second dimension of a 2D array, while the first dimension contains the frequency distribution of distances of randomly generated point pairs (the D2 distribution). The resulting descriptor, D2a, is a two-dimensional histogram that incorporates two shape features: The ratio of face areas and the distance between two random points. © Springer-Verlag Berlin Heidelberg 2007.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/77982
ISBN: 9783540694212
ISSN: 03029743
DOI: 10.1007/978-3-540-69423-6_6
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