Publications by authors named "Ayush Bhargava"

With the popularity of Virtual Reality (VR) on the rise, creators from a variety of fields are building increasingly complex experiences that allow users to express themselves more naturally. Self-avatars and object interaction in virtual worlds are at the heart of these experiences. However, these give rise to several perception based challenges that have been the focus of research in recent years.

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The availability of new and improved display, tracking and input devices for Virtual Reality experiences has facilitated the use of partial and full body self-avatars in interaction with virtual objects in the environment. However, scaling the avatar to match the user's body dimensions remains to be a cumbersome process. Moreover, the effect of body-scaled self-avatars on size perception of virtual handheld objects and related action capabilities has been relatively unexplored.

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Calibration is the process by which the execution of actions becomes scaled to the (changing) relationship between environmental features and the actor's action capabilities. Though much research has investigated how individuals calibrate to perturbed optic flow, it remains unclear how different experimental factors contribute to the magnitude of calibration transfer. In the present study, we assessed how testing environment (Experiment 1), an adapted pretest-calibration-posttest design (Experiment 2), and bilateral ankle loading (Experiment 3) affected the magnitude of calibration to perturbed optic flow.

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Actors utilize intrinsically scaled information about their geometric and dynamic properties when perceiving their ability to pass through openings. Research about dynamic factors of affordance perception have shown that the reliability of a given movement, or the precision of one's motor control for that movement, increase the buffer space used when interacting with the environment. While previous work has assessed motor control reliability as a person-level variable (i.

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With costs of head-mounted displays (HMDs) and tracking technology decreasing rapidly, various virtual reality applications are being widely adopted for education and training. Hardware advancements have enabled replication of real-world interactions in virtual environments to a large extent, paving the way for commercial grade applications that provide a safe and risk-free training environment at a fraction of the cost. But this also mandates the need to develop more intrinsic interaction techniques and to empirically evaluate them in a more comprehensive manner.

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