High-Fidelity Avatar Eye-Representation

Abstract

In collaborative virtual environments, the visual representation of avatars has been shown to be an important determinant of participant behaviour and response. We explored the influence of varying conditions of eye-representation in our high-fidelity avatar by measuring how accurately people can identify the avatar's point-of- regard (direction of gaze), together with subjective authenticity assessments of the avatar's behaviour and visual representation. The first of two variables investigated was socket-deformation, which is to say that our avatar's eyelids, eyebrows and surrounding areas morphed realistically depending on eye-rotation. The second was vergence of our avatar's eyes to the exact point-of-regard. Our results suggest that the two variables significantly influence the accuracy of point-of-regard identification. This accuracy is highly dependent on the combination of viewing-angle and the point-of-regard itself. We found that socket-deformation in particular has a highly positive impact on the perceived authenticity of our avatar's overall appearance, and when judging just the eyes. However, despite favourable subjective ratings, overall performance during the point-of-regard identification task was actually worse with the highest quality avatar. This provides more evidence that as we move forward to using higher fidelity avatars, there will be a tradeoff between supporting realism of representation and supporting the actual communicative task.