Creation of a new set of dynamic virtual reality faces for the assessment and training of facial emotion recognition ability
Creation of a new set of dynamic virtual reality faces for the assessment and training of facial emotion recognition ability
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DOI：
10.1007/s10055-013-0236-7
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发表时间：
2014-03-01
期刊：
影响因子：
4.2
通讯作者：
Gonzalez-Conde, Joan
中科院分区：
文献类型：
--
作者：
Gutierrez-Maldonado, Jose;Rus-Calafell, Mar;Gonzalez-Conde, Joan
在治疗社交障碍患者时，识别面部情绪的能力是目标行为。在评估这种能力时，最广泛使用的面部刺激是照片。尽管照片的使用已经被证明是有效的，但照片无法捕捉到人类表情的动态方面。这一限制可以通过创建具有可行的表达情感的虚拟代理来克服。本研究的主要目的是创建一套新的具有高度真实感的动态虚拟面孔，可以整合到虚拟现实(VR)网络干预中，以训练精神分裂症患者的全部社交技能。基于人脸动作编码系统创建了一组高真实感的虚拟人脸。还包括面部运动动画，以模拟人类面部表情的动态。连续的健康参与者(n=98)完成了一项面部情绪识别任务，他们使用自然面孔(照片)和表达五种基本情绪加上一种中性情绪的虚拟代理人。重复测量方差分析显示，在两种呈现条件下，参与者的识别准确率没有显著差异。然而，愤怒在VR图像中被更好地识别，厌恶在照片中被更好地识别。年龄，参与者的性别和反应时间也被调查了。讨论了在网络干预中使用具有真实人类表情的虚拟代理人的意义。
The ability to recognize facial emotions is target behaviour when treating people with social impairment. When assessing this ability, the most widely used facial stimuli are photographs. Although their use has been shown to be valid, photographs are unable to capture the dynamic aspects of human expressions. This limitation can be overcome by creating virtual agents with feasible expressed emotions. The main objective of the present study was to create a new set of dynamic virtual faces with high realism that could be integrated into a virtual reality (VR) cyberintervention to train people with schizophrenia in the full repertoire of social skills. A set of highly realistic virtual faces was created based on the Facial Action Coding System. Facial movement animation was also included so as to mimic the dynamism of human facial expressions. Consecutive healthy participants (n = 98) completed a facial emotion recognition task using both natural faces (photographs) and virtual agents expressing five basic emotions plus a neutral one. Repeated-measures ANOVA revealed no significant difference in participants' accuracy of recognition between the two presentation conditions. However, anger was better recognized in the VR images, and disgust was better recognized in photographs. Age, the participant's gender and reaction times were also explored. Implications of the use of virtual agents with realistic human expressions in cyberinterventions are discussed.