Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33536
Title: Recovering the 3D shape and poses of face images based on the similarity transform
Authors: Koo, HS
Lam, KM 
Keywords: 3D reconstruction
Face recognition
Genetic algorithm
Similarity transform
Issue Date: 2008
Publisher: North-Holland
Source: Pattern recognition letters, 2008, v. 29, no. 6, p. 712-723 How to cite?
Journal: Pattern recognition letters 
Abstract: In this paper, a new algorithm is proposed to derive the 3D structure of a human face from a group of face images under different poses. Based on the corresponding 2D feature points of the respective images, their respective poses and the depths of the feature points can be estimated based on measurements using the similarity transform. To accurately estimate the pose of and the 3D information about a human face, the genetic algorithm (GA) is applied. Our algorithm does not require any prior knowledge of camera calibration, and has no limitation on the possible poses or the scale of the face images. It also provides a means to evaluate the accuracy of the constructed 3D face model based on the similarity transform of the 2D feature point sets. Our approach can also be extended to face recognition to alleviate the effect of pose variations. Experimental results show that our proposed algorithm can construct a 3D face structure reliably and efficiently.
URI: http://hdl.handle.net/10397/33536
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/j.patrec.2007.11.018
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