Adaptive 3D facial action intensity estimation and emotion recognition
We estimate AU intensity based on mRMR-based feature selection. Adaptive ensemble classifiers are proposed for robust expression classification. The ensemble models show superior ability for novel emotion class detection. Both database images and real human subjects are used to evaluate the system. It outperforms related work reported in the literature for the Bosphorus database.
adaptive ensemble classifiers facial emotion recognition action unit intensity estimation complementary neural networks support vector regression support vector classification