预动环境中基于协同信任的表情分析

面向情感计算的面部表情研究得到快速发展,人机交互中得到表情的可信分析成为研究热点.提出预动环境中协同依赖的表情分析模型,设计协同信任算法,实现对表情的可信分析.首先,根据个体的表情结构与特征证据的关系提出预动环境中可协同交互的表情分析模型；然后,引入协同理论扩展特征证据,设计协同依赖的可信表情模型,阐述表情特征的证据推理算法;最后通过实验验证协同信任模型对表情的实时可信分析,降低了分析模型主观因素对可信结果的影响.该研究有助于更好地认识信任因素对情感计算的影响.

Facial Expression Analysis Based on Synergetic Trust Model in Proactive Environment

With the rapid development of affective computing and facial expression analysis,it is important to understand trusted facial expressions during human-computer interaction.This paper presents a novel approach for synergetic trust analysis of facial expression.Based on the cooperative mechanism between facial expression features and affective trust evidences,the synergy theory is applied to extend the evidences and to achieve the reasoning algorithm in a proactive environment.The resultant model from cooperative interaction and synergetic dependence evaluation is potentially capable of analyzing the trusted facial expression.Experiments have been conducted to evaluate the rationality of the approach.It is suggested that synergetic trust model can reduce the subjective impacts of overall analysis and perform at a higher credibility can allow the user to further comprehend affective computing with trust factors.