Facial Expression Recognition with Multi-channel Deconvolution

Facial expression recognition is an important task in human computer interaction systems to include emotion processing. In this work we present a multi-channel deconvolution method for post processing of face expression data derived from video sequences. Photogrammetric techniques are applied to determine real world geometric measures and to build the feature vector. SVM classification is used to classify a limited number of emotions from the feature vector. A multi-channel deconvolution removes ambiguities at the transitions between different classified emotions. This way, typical temporal behavior of facial expression change is considered.