Construction of emotional space from facial expression by parallel sand glass type neural networks

We proposed a parallel sand glass type neural network. The network model can learn some people's facial expressions. This network has some five-layered neural networks and hidden neurons in each third layer are connected. Our proposed network model can construct an emotional space based on facial expressions. This emotional space is similar to the emotional circle of Ekman et al. (1972). However, there is a weak point in learning facial. expressions of a lot of people, because the learning algorithm requires a five-layered network for learning faces of a person. We improved the learning algorithm in only a two-combined network. To verify the validity of proposed network model, we experimented facial expressions of some people.