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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 249847, 8 pages
http://dx.doi.org/10.1155/2013/249847
Research Article

Differential and Statistical Approach to Partial Model Matching

School of Information Science and Engineering, Central South University, Changsha 410083, China

Received 2 December 2012; Accepted 23 December 2012

Academic Editor: Sheng-Yong Chen

Copyright © 2013 Kehua Guo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Partial model matching approaches are important to target recognition. In this paper, aiming at a 3D model, a novel solution utilizing Gaussian curvature and mean curvature to represent the inherent structure of a spatial shape is proposed. Firstly, a Point-Pair Set is constructed by means of filtrating points with a similar inherent characteristic in the partial surface. Secondly, a Triangle-Pair Set is demonstrated after locating the spatial model by asymmetry triangle skeleton. Finally, after searching similar triangles in a Point-Pair Set, optimal transformation is obtained by computing the scoring function in a Triangle-Pair Set, and optimal matching is determined. Experiments show that this algorithm is suitable for partial model matching. Encouraging matching efficiency, speed, and running time complexity to irregular models are indicated in the study.