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An analysis of facial movement tracking in ordinary human-computer interaction

机译:普通人机交互中的面部运动跟踪分析

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Automatic tracking of facial movement is potentially important as a non-invasive source of physiological data in Affective Computing applications. Facial movement tracking software is becoming commercially available and affordable. This paper explores the association between facial and physiological responses to computer-based events, and the viability of facial movement tracking in detecting and distinguishing qualitative differences in users' facial movements under normal conditions of computer use. Fifteen participants took a web-based quiz. The quiz contained two relatively ordinary HCI events as stimuli: an alert intended to evoke surprise, and questions with high affective content intended to evoke amusement. From previous findings, the alert was expected to be the stronger of the two stimuli. Participants' physiological arousal was recorded and their faces videoed. The videos for the periods around each event were analysed by commercially available facial movement tracking software. Human judges considered participants' faces to have responded to both stimuli, but more to the stronger of the two stimuli. Facial response did not always concur with physiological arousal. The tracker detected reactions to the stronger stimulus but had mixed success with the weaker stimulus. The tracker also generated different data profiles for two different facial expressions. These findings support the supposition that users' facial expressions can and do respond to ordinary computer-based events, and indicate that facial movement tracking is becoming a viable technique, and is available to non-computer vision specialists.
机译:在情感计算应用程序中,作为非侵入性生理数据源,自动跟踪面部运动可能非常重要。面部运动跟踪软件正变得商业化并负担得起。本文探讨了对计算机事件的面部和生理反应之间的关联,以及在正常使用计算机的情况下,面部运动跟踪在检测和区分用户面部运动的质量差异方面的可行性。 15名参与者参加了基于网络的测验。测验包含两个相对普通的HCI事件作为刺激:旨在引起惊喜的警报以及具有引起情感娱乐性的高情感内容。根据以前的发现,预计警报将是两种刺激中的一种。记录参与者的生理唤醒,并记录他们的面部视频。通过市售的面部运动跟踪软件对每个事件前后的视频进行了分析。人类法官认为参与者的脸对两种刺激都做出了反应,但对两种刺激中的较强者做出了更多反应。面部反应并不总是与生理唤醒有关。跟踪器检测到了对较强刺激的反应,但对较弱刺激却取得了成功。跟踪器还为两个不同的面部表情生成了不同的数据配置文件。这些发现支持这样一种假设,即用户的面部表情可以并且确实能够响应基于计算机的普通事件,并且表明面部运动跟踪正在成为一种可行的技术,并且可供非计算机视觉专家使用。

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