Learning and analysis of facial expression images using a five-layered hourglass-type neural network
説明
In this study, a method to perform feature extraction and image creation support of five facial human expressions in gray scale images are presented in which the five-layered hourglass-type neural network is used. Input values to the neural network are five facial expression images composed of 100/spl times/100 pixels and are the same as the teacher-signals in the output layer. The teacher-signals are learned using the five-layered hourglass-type neural network to achieve a compression function and restoration of the images. The compressed information and causality of each facial expression are dealt with in the third layer (the emotion-layer). Furthermore, it can be shown that an image creation is performed by giving adequate values to the emotion-layer.
収録刊行物
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- IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028)
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IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028) 5 373-376, 2003-01-20
IEEE