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Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 178102, 6 pages
http://dx.doi.org/10.1155/2015/178102
Research Article

A Multiscale Constraints Method Localization of 3D Facial Feature Points

1College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an 710054, China
2School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
3School of Information Technology, Luoyang Normal University, Luoyang 471022, China

Received 30 March 2015; Revised 7 June 2015; Accepted 23 June 2015

Academic Editor: Edite Figueiras

Copyright © 2015 Hong-an Li 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

It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms.