State-of-the-art of 3D facial reconstruction methods for face recognition based on a single 2D training image per person

3D facial reconstruction systems attempt to reconstruct 3D facial models of individuals from their 2D photographic images or video sequences. Currently published face recognition systems, which exhibit well-known deficiencies, are largely based on 2D facial images, although 3D image capture systems...

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Bibliographic Details
Published in:	Pattern recognition letters Vol. 30; no. 10; pp. 908 - 913
Main Authors:	Levine, Martin D., (Chris) Yu, Yingfeng
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 15.07.2009 Elsevier
Subjects:	3D morphable model 3D reconstruction Applied sciences Artificial intelligence Computer science; control theory; systems Exact sciences and technology Face recognition Image processing Information, signal and communications theory Pattern recognition Pattern recognition. Digital image processing. Computational geometry Signal processing Single 2D training image State-of-the-art Telecommunications and information theory 3D morphable model 3D reconstruction Face recognition Single 2D training image State-of-the-art Biometrics State of the art Photographic image Image processing Video signal state-of-the-art Stochastic method Volume reconstruction Texture Learning Image matching Image sequence Computer graphics Newton method Computer vision Sequence alignment Error function Pattern recognition Algorithm Interactive system Photography Three dimensional model Tridimensional image Automatic recognition
ISSN:	0167-8655, 1872-7344
Online Access:	Get full text
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