In this paper, in order to achieve high-speed PCA, the simple principal component analysis (SPCA) is applied to compress the dimensionality of portions that constitute a face. By using neural networks, the difference in the value of cos θ between the true and the false smiles is clarified and the true smile is discriminated. Finally, in order to show the effectiveness of the proposed face classification method for true or false smiles, computer simulations are done with real images.
主成分分析を高速化したSimple PCAとNeural Networksを用いる新たな認識手法を提案した．提案手法を用いて，表情の一つである笑顔の真偽分類と他の表情との識別をコンピュータシミュレーションで行い，実験結果を考察したものである．A4版 全52頁 英文，中野実代子
