Abstract
BackgroundComputer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups.Methodology/Principal FindingsThirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition.Conclusions/SignificanceVirtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications.
Highlights
The recognition of emotions from others’ faces is a universal and fundamental skill for social interaction [1,2]
Paired t-tests revealed that reaction times (RTs) were significantly slower for neutral (t[31] = 8.38, p = .002) and for happy faces (t[31] = 4.03, p,.0001) when a virtual compared to a natural face had to be recognized
A correlation analysis discarded the possibility of a speed-accuracy trade-off for any emotion; for neutral and happy facial expressions a negative relation between RT and accuracy emerged: the faster subjects responded, the higher was the rate of accuracy
Summary
The recognition of emotions from others’ faces is a universal and fundamental skill for social interaction [1,2]. Increasing research has been dedicated to psychophysics, neural processing and impairments of emotion recognition. In most instances those studies applied still photographs of facial expressions as experimental stimuli. Recent imaging studies indicate that neural activity is enhanced and more distributed when dynamically morphed relative to static facial expressions are presented to subjects [4,5]. Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. The validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups
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