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Mathematical Problems in Engineering
Volume 2015, Article ID 678973, 10 pages
Research Article

Robust Head Pose Estimation Using a 3D Morphable Model

1School of Computer Science, Sichuan University, Chengdu 610064, China
2Wisesoft Software Co., Ltd., Chengdu 610045, China
3College of Information Engineering, Sichuan Agricultural University, Ya’an 625014, China
4School of Aeronautics and Astronautics, Sichuan University, Chengdu 610064, China

Received 30 September 2014; Accepted 17 November 2014

Academic Editor: Hui Zhang

Copyright © 2015 Ying Cai 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.


Head pose estimation from single 2D images has been considered as an important and challenging research task in computer vision. This paper presents a novel head pose estimation method which utilizes the shape model of the Basel face model and five fiducial points in faces. It adjusts shape deformation according to Laplace distribution to afford the shape variation across different persons. A new matching method based on PSO (particle swarm optimization) algorithm is applied both to reduce the time cost of shape reconstruction and to achieve higher accuracy than traditional optimization methods. In order to objectively evaluate accuracy, we proposed a new way to compute the pose estimation errors. Experiments on the BFM-synthetic database, the BU-3DFE database, the CUbiC FacePix database, the CMU PIE face database, and the CAS-PEAL-R1 database show that the proposed method is robust, accurate, and computationally efficient.