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Bias analyses of spontaneous facial expression database

机译:自发性面部表情数据库的偏见分析

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In this paper, cross-corpora evaluations are used to analyze the bias of spontaneous facial expression databases. Local binary pattern, Gabor, eigenface and fisherface features are extracted and applied to the four spontaneous expression databases: USTC-NVIE, VAM, Belfast Naturalistic and SEMAINE to recognize arousal (high/low) and valance (positive/negative) respectively. Experimental results indicate that there exists bias among different spontaneous expression databases. The emotion-induction methods, the variety of subjects and the quantity of raters may have caused such a bias.
机译:在本文中,跨语料库评估用于分析自发面部表情数据库的偏差。提取本地二进制模式,Gabor,本征面和鱼面特征并将其应用于四个自发表达数据库:USTC-NVIE,VAM,Belfast Naturalistic和SEMAINE,分别识别唤醒(高/低)和价数(正/负)。实验结果表明,不同的自发表达数据库之间存在偏差。诱导情绪的方法,主题的多样性和评估者的数量可能导致了这种偏见。

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