An emotion generation model based on random graphs Online publication date: Fri, 16-Jul-2010
by Chao-gang Wan, Jie-yu Zhao, Yuan-yuan Zhang
International Journal of Computer Applications in Technology (IJCAT), Vol. 38, No. 1/2/3, 2010
Abstract: Emotions are an indispensable aspect in harmonious human–computer interaction and artificial intelligence. In this paper, we present an algorithm to generate emotions and show them with 3D facial expression animation. The Pleasure-Arousal-Dominance (PAD) emotion space is used to define the affective elements of exterior stimuli and interior emotional states. A stochastic graphical model is designed to represent the relationships between the emotion, the mood and the personality. Finally, we build a mapping from the emotion space to the facial expression space with a competitive learning network. The facial expression is vividly shown by a 3D virtual human head. The experimental results demonstrate that our emotion generation model works effectively and meets the basic principle of human emotion generation.
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