Perception of Looming Motion in Virtual Reality Egocentric Interception Tasks.

Motion in depth is commonly misperceived in Virtual Reality (VR), making it difficult to intercept moving objects, for example, in games. We investigate whether motion cues could be modified to improve these interactions in VR. We developed a time-to-contact estimation task, in which observers ($n=18$n=18) had to indicate by button press when a looming virtual object would collide with their head. We show that users consistently underestimate speed. We construct a user-specific model of motion-in-depth perception, and use this model to propose a novel method to modify monocular depth cues tailored to the specific user, correcting individual response errors in speed estimation. A user study was conducted in a simulated baseball environment and observers were asked to hit a looming baseball back in the direction of the pitcher. The study was conducted with and without intervention and demonstrates the effectiveness of the method in reducing interception errors following cue modifications. The intervention was particularly effective at fast ball speeds where performance is most limited by the user's sensorimotor constraints. The proposed approach is easy to implement and could improve the user experience of interacting with dynamic virtual environments.