Freitag, 4.12.15, 10:30 Uhr, WE5/05.013

Teena Hassan & Dominik Seuss (Fraunhofer IIS & Cognitive Systems Group): Automatic Facial Action Unit Detection

Facial expressions are social signals that could reveal an underlying emotional state or physiological condition. They are a key component of nonverbal behavioral analysis. Psychologists have developed a comprehensive framework for analyzing facial expressions through the basic visually distinguishable motions of facial muscles. The framework is called Facial Action Coding System (FACS) and the basic facial movements are called Action Units (AU). The framework allows an objective analysis of facial expressions by coding any facial expression as a combination of AUs along with their intensities.

In this project, we use a model-based approach to infer AU intensities from videos of facial expressions. We use a 3D deformable model of human facial geometry that describes the person-dependent and expression-related shape variations. We combine information about facial geometry and facial appearance in a state estimation framework to infer AU intensities. A motion model based on the viscoelastic properties of facial muscles is used to model the changes in AU intensities over time.

In this presentation, we will provide an overview of the approach, present some evaluation results, and briefly discuss the next steps.