In this paper, in order for PCA to become high-speed, the simple principal component analysis (SPCA) is applied compress the dimensionality of portions that constitute a face. By using Neural Networks, the value of cos _ between true and false (plastic) smiles is clarified and the true smile is discriminated. For the result, the rate of a classification using NN was 90.6% as the whole. In conclusion, it is confirmed that the proposed method works very well.
Simple PCAとニューラルネットワークスを用いて，表情の一つである笑顔の真偽分類をコンピュータシミュレーションで行った．データの正規化を行うことで実験の精度が向上した．
共同発表者：Miyoko Nakano,Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu.
