Abstract
This study investigates effectiveness of a local high-fidelity 3D facial avatar for a global audience by observing how US and International student groups differed in identifying subjects and perceiving emotions while viewing nonverbal high-fidelity 3D facial avatar animations embedded with the motion data of three US individuals. To synthesize the animated 3D avatars to convey highly believable facial expressions, a 3D scanned facial model was mapped with high-fidelity motion-capture data of three native US subjects as they spoke designated English sentences with specified emotions. Simple animations in conjunction with actual footage of the subjects speaking during the facial motion-capture sessions were shown several times to both native US and international students in similar settings. After a familiarization process, we showed the students randomly arranged talking avatars without voices and asked them to identify the corresponding identities and emotional types of the subjects whose facial expressions were utilized in the creation of the avatars, and to rate their confidence in their selections. We found that the US group had higher success rates in subject identification, although the related difference in confidence ratings between two groups was not significant. The differences in the success rates and confidence ratings on the perception of emotion between the two groups were not significant either. The results of our study provide interesting insights into avatar-based interaction where the national and/or cultural background of a person impacts the perception of identity while having little effect on the perception of emotion. However, we observed that dynamics (e.g., head motion) could offset the disadvantage of cultural unfamiliarity in subject identification. We observed that both groups performed at a nearly identical level in subject identification and emotion perception when they were shown the avatar animation with heightened expression and dynamic intensities. In addition, we observed that the confidence ratings were correlated to accuracy in identifying the subject but not to accuracy in perceiving emotion.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications
Cited by
11 articles.
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