New method for designing face image classifiers using 3-D CG model
Shigeru Akamatsu, Tsutomu Sasaki, N. Masui, Hideo Fukamachi, Yasuhito Suenaga · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
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.