Accuracy of three commercial automatic emotion recognition systems across different individuals and their facial expressions

Damien Dupré, Nicole Andelic, Gawain Morrison, G. McKeown
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引用次数: 19

Abstract

Automatic facial expression recognition systems can provide information about our emotions and how they change over time. However, based on different statistical methods the results of automatic systems have not yet been compared. In the current paper we evaluate the emotion detection between three different commercial systems (i.e. Affectiva, Kairos and Microsoft) when detecting dynamic and spontaneous facial expressions. Even if the study was performed on a limited sample of videos, the results show significant differences between the systems for the same video and per system across comparable facial expressions. Finally, we reflect on the implications according the generalization of the results provided by automatic emotion detection.
三种商用自动情绪识别系统对不同个体及其面部表情的准确性
自动面部表情识别系统可以提供有关我们的情绪以及它们如何随时间变化的信息。然而,基于不同的统计方法,尚未对自动系统的结果进行比较。在本文中,我们评估了三个不同的商业系统(即Affectiva, Kairos和Microsoft)在检测动态和自发面部表情时的情绪检测。即使这项研究是在有限的视频样本上进行的,结果也显示出相同视频的系统之间和不同系统之间在可比较的面部表情上的显著差异。最后,我们根据自动情绪检测提供的结果的泛化来反思其意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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