1 November 1991 New method for designing face image classifiers using 3-D CG model
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Abstract
This paper proposes a new approach for designing robust pattern classifiers for human face images with the aid of a state-of-the-art 3-D imaging technique. The 3-D CG models of human faces are obtained using a new 3-D scanner. A database of synthesized face images simulating diverse imaging conditions is automatically constructed from the 3-D CG model of the subject's face by generating a series of images while varying the image synthesis parameters. The database is successfully applied to the extraction of a pair-wise discriminant that achieves higher class separability against real face images of two subjects acquired under disparate imaging conditions. The use of the 3-D CG model in training a classifier is shown to yield more accurate face recognition in the framework of 2-D image matching.
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Shigeru Akamatsu, Tsutomu Sasaki, Nobuhiko Masui, Hideo Fukamachi, Yasuhito Suenaga, "New method for designing face image classifiers using 3-D CG model", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50398; https://doi.org/10.1117/12.50398
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