Abstract
In this paper, the authors describe a method for the identification of human faces. In this method, the fiber grating (FG) vision sensor which has been developed by the authors is employed for the three dimensional shape of the faces. Before the identification of the face using the three dimensional shape of the face, it is necessary to calibrate the position and direction of the facial data. In this method, a set of the directions of normal vectors at data points in the facial surface is obtained, and calibrations are carried out in accordance with the extend of errors in the sets. To identify human faces, a multilayered neural network is used in which the inputs are two component values of normal vector at data spot in the facial surface. An experiments using an experimental system is performed to demonstrate the efficacy of this method and the experimental results are shown.
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