Influence of Dynamic Field of View Restrictions on Rotation Gain Perception in Virtual Environments

Abstract

The perception of rotation gain, defined as a modification of the virtual rotation with respect to the real rotation, has been widely studied to determine detection thresholds and widely applied to redirected navigation techniques. In contrast, Field of View (FoV) restrictions have been explored in virtual reality as a mitigation strategy for motion sickness, although they can alter user's perception and navigation performance in virtual environments. This paper explores whether the use of dynamic FoV manipulations, referred also as vignetting, could alter the perception of rotation gains during virtual rotations in virtual environments (VEs). We conducted a study to estimate and compare perceptual thresholds of rotation gains while varying the vignetting type (no vignetting, horizontal and global vignetting) and the vignetting effect (luminance or blur). 24 Participants performed 60 or 90 degrees virtual rotations in a virtual forest, with different rotation gains applied. Participants have to choose whether or not the virtual rotation was greater than the physical one. Results showed that the point of subjective equality was different across the vignetting types, but not across the vignetting effect or the turns. Subjective questionnaires indicated that vignetting seems less comfortable than the baseline condition to perform the task. We discuss the applications of such results to improve the design of vignetting for redirection techniques.

A review of cybersickness in head-mounted displays: raising attention to individual susceptibility

“…Dynamic FOV restrictors can be influenced by motion characteristics such as velocity, acceleration, or the magnitude of optical flow . Norouzi et al (2018) (Brument et al 2020). It may be due to the reason that the central area triggers more discomfort than the peripheral area during lateral motion (Pöhlmann et al 2021).…”

Avoiding virtual humans in a constrained environment: Exploration of novel behavioural measures

“…Behavioral responses can be reflected in the choice the person makes in the experimental condition, e.g., approaches a specific virtual character in a crowd of characters [3]. Other examples of behavioral measures include analysis of eye-gaze behavior (e.g., number of gaze fixations onto a character) [28,29,30] and analysis of human locomotion.…”

“…Before analysing the trajectory, we applied some standard treatment to the trajectory data we collected, e.g., removing artefacts such as medio-lateral oscillations due to stepping activity and frame drops from the raw trajectory path. Since the simulation did not have a constant rate, we temporally resampled the data at 40 fps and applied a Butterworth low-pass filter with a cutoff frequency of 1 Hz [28].…”

Studying the Influence of Translational and Rotational Motion on the Perception of Rotation Gains in Virtual Environments

“…To this end, many research work focused on the impact of different experimental conditions on the perception of head rotations gains in VR. For instance, the type of rotation [Jerald et al 2008;, the amount of rotation to perform [Bruder et al 2009], the gain implementation [Congdon and Steed 2019;Zhang and Kuhl 2013], the impact of visual [Bruder et al 2012b;Paludan et al 2016] or auditory cues [Nilsson et al 2016;Serafin et al 2013] or distractors [Peck et al 2009;Williams and Peck 2019], the impact of restricted Field of Views [Bolte et al 2010;Brument et al 2020;Williams and Peck 2019], difference between CAVE and HMD (Head-Mounted Displays) [Ragan et al 2016], for video-based 360 • telepresence systems [Matsumoto et al 2020;Zhang et al 2018], different locomotion interfaces [Bruder et al 2012a] or even the method to estimate users perception of rotation gains [Hutton et al 2018] have been explored so far. Nilsson et al 2018] survey these studies and you can refer to them for further information.…”