A dynamic curvature based approach for facial activity analysis in 3D space

This paper presents a novel dynamic curvature based approach (dynamic shape-index based approach) for 3D face analysis. This method is inspired by the idea of 2D dynamic texture and 3D surface descriptors. The dynamic texture (DT) based approaches [30][31][32] encode and model the local texture features in the temporal axis, and have achieved great success in applications of 2D facial expression recognition. In this paper, we propose a so-called Dynamic Curvature (DC) approach for 3D facial activity analysis. To do so, the 3D dynamic surface is described by its surface curvature-based shape-index information. The surface features are characterized in local regions along the temporal axis. A dynamic curvature descriptor is constructed from local regions as well as temporal domains. To locate the local regions, we also applied a 3D tracking model based method for detecting and tracking 3D features across 3D dynamic sequences. Our method is validated through our experiment on 3D facial activity analysis for distinguishing neutral vs. non-neutral expressions, prototypic expressions, and their intensities.