Perceptual Comparison of Procedural and Data-Driven Eye Motion Jitter

Abstract

Research has shown that keyframed eye motions are perceived as more realistic when some noise is added to eyeball motions and to pupil size changes. We investigate whether this noise, in contrast to being motion captured, can be synthesized with standard techniques, e.g., procedural or data-driven approaches. In a two-alternative forced choice task, we compare eye animations created with four different techniques: motion captured, procedural, data-driven, and keyframed (lacking noise). Our perceptual experiment uses three character models with different levels of realism and two motions. Our results suggest that procedural and data-driven noise can be used to create animations at similar perceived naturalness to our motion captured approach. Participants’ eye movements when viewing the animations show that animations without jitter yielded fewer fixations, suggesting ease of dismissal as unnatural.