Facial Expression Recognition Using a Neural Network
Christine Lisetti, David E. Rumelhart · 1998
We discuss the development of a neural network for fa-cial expression recognition. It aims at recognizing and interpreting facial expressions in terms of signaled emo-tions and level of expressiveness. We use the backprop-agation algorithm to train the system to differentiate between facial expressions. We show how the network generalizes to new faces and we analyze the results. In our approach, we acknowledge that facial expressions can be very subtle, and propose strategies to deal with the complexity of various levels of expressiveness. Our database includes a variety of different faces, including individuals of different gender, race, and including dif-ferent features such as glasses, mustache, and beard. Even given the variety of the database, the network learns fairly succesfuily to distinguish various levels of expressiveness, and generalizes on new faces as ~ell.