Natural Facial Expression Recognition Using Dynamic and Static Schemes

Abstract. Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users ’ affective state. The current paper addresses the problem of facial ex-pression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Fur-thermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Anal-ysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences.