Facial Expression Synthesis Using PAD Emotional Parameters for a Chinese Expressive Avatar

Facial expression plays an important role in face to face communication in that it conveys nonverbal information and emotional intent beyond speech. In this paper, an approach for facial expression synthesis with an expressive Chinese talking avatar is proposed, where a layered parametric framework is designed to synthesize intermediate facial expressions using PAD emotional parameters [5], which describe the human emotional state with three nearly orthogonal dimensions. Partial Expression Parameter (PEP) is proposed to depict the facial expression movements in specific face regions, which act as the mid-level expression parameters between the low-level Facial Animation Parameters (FAPs) [11] and the high-level PAD emotional parameters. A pseudo facial expression database is established by cloning the real human expression to avatar and the corresponding emotion states for each expression is annotated using PAD score. An emotionexpression mapping model is trained on the database to map the emotion state (PAD) into facial expression configuration (PEP). Perceptual evaluation shows the input PAD value is consistent with that of human perception on synthetic expression, which supports the effectiveness of our approach.