The Effects of Head-Centric Rest Frames on Egocentric Distance Perception in Virtual Reality

Abstract

It has been shown through several research investigations that users tend to underestimate distances in virtual reality (VR). Virtual objects that appear close to users wearing a Head-mounted display (HMD) might be located at a farther distance in reality. This discrepancy between the actual distance and the distance observed by users in VR was found to hinder users from benefiting from the full in-VR immersive experience, and several efforts have been directed toward finding the causes and developing tools that mitigate this phenomenon. One hypothesis that stands out in the field of spatial perception is the rest frame hypothesis (RFH), which states that visual frames of reference (RFs), defined as fixed reference points of view in a virtual environment (VE), contribute to minimizing sensory mismatch. RFs have been shown to promote better eye-gaze stability and focus, reduce VR sickness, and improve visual search, along with other benefits. However, their effect on distance perception in VEs has not been evaluated. To explore and better understand the potential effects that RFs can have on distance perception in VR, we used a blind walking task to explore the effect of three head-centric RFs (a mesh mask, a nose, and a hat) on egocentric distance estimation. We performed a mixed-design study where we compared the effect of each of our chosen RFs across different environmental conditions and target distances in different 3D environments. We found that at near and mid-field distances, certain RFs can improve the user\u27s distance estimation accuracy and reduce distance underestimation. Additionally, we found that participants judged distance more accurately in cluttered environments compared to uncluttered environments. Our findings show that the characteristics of the 3D environment are important in distance estimation-dependent tasks in VR and that the addition of head-centric RFs, a simple avatar augmentation method, can lead to meaningful improvements in distance judgments, user experience, and task performance in VR

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