Novel representation for driver emotion recognition in motor vehicle videos

摘要

A novel feature representation of human facial expressions for emotion recognition is developed. The representation leveraged the background texture removal ability of Anisotropic Inhibited Gabor Filtering (AIGF) with the compact representation of spatiotemporal local binary patterns. The emotion recognition system incorporated face detection and registration followed by the proposed feature representation: Local Anisotropic Inhibited Binary Patterns in Three Orthogonal Planes (LAIBP-TOP) and classification. The system is evaluated on videos from Motor Trend Magazine's Best Driver Car of the Year 2014-2016. The results showed improved performance compared to other state-of-the-art feature representations.