Shape Topics: A Compact Representation and New Algorithms for 3D Partial Shape Retrieval

This paper develops an efficient new method for 3D partial shape retrieval. First, a Monte Carlo sampling strategy is employed to extract local shape signatures from each 3D model. After vector quantization, these features are represented by using a bag-of-words model. The main contributions of this paper are threefold as follows: 1) a partial shape dissimilarity measure is proposed to rank shapes according to their distances to the input query, without using any timeconsuming alignment procedure; 2) by applying the probabilistic text analysis technique, a highly compact representation "Shape Topics" and accompanying algorithms are developed for efficient 3D partial shape retrieval, the mapping from "Shape Topics" to "object categories" is established using multi-class SVMs; and 3) a method for evaluating the performance of partial shape retrieval is proposed and tested. To our best knowledge, very few existing methods are able to perform well online part...

• Type: Conference
• Year: 2006
• Where: CVPR
• Authors: Yi Liu, Hongbin Zha, Hong Qin
• Keywords: Computer Vision, CVPR 2006, Large 3d Shape, Local Shape Signatures, Online Partial Shape, Partial Shape Dissimilarity, Partial Shape Retrieval