| 摘要 |
<P>PROBLEM TO BE SOLVED: To provide a face recognition system capable of absorbing fluctuation of position/angle of a face or fluctuation of illumination and performing efficient learning and recognition even in case that the number of identification objects is increased. <P>SOLUTION: A neural network NN is divided to a plurality of sub-nets, as shown in the drawing, to perform learning and recognition in parallel in sub-net units. In configuration of a parallel NN, it is permitted that the same facial pattern fuzzily attributes to a plurality of sub-nets, considering the ambiguity of patterns. According to this, relatively close patterns can be always efficiently recognized in the same sub-net. The facial pattern of an identification object is acquired as a there-dimensional image by a three-dimensional shape measuring device. Therefore, an input face pattern corrected while eliminating an influence such as a change in position or attribute of the person or a fluctuation of lighting as much as possible can be obtained, and a face recognition system robust to the rotation of a face is realized. <P>COPYRIGHT: (C)2006,JPO&NCIPI |
