人の顔の6基本表情のニューラルネットワーク認識における特性分析

概要

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In order to develop "active human interface" that realizes emotive communication between intelligent machines and humans, we have been investigating machine recognition of human emotions from facial expressions. Using a neural network (NN), we have already obtained a high correct recognition ratio of about 90% for 6 basic facial expressions, but we find that depending on the NN learning information, there exist certain characteristics in misrecognition and correct recognition ratio. This paper analyzes these characteristics using action units (AUs) employed in the psychological field for describing the basic muscle movements of human face and analyzing the relationship between the NN input and output information. We present, in this paper, the reason why misrecognition occurs by using the Jacobian of the NN-input -output function and how AUs influence the recognition results by assigning a zero value to each AU using NN input information.
一般社団法人日本機械学会の論文
1995-02-25