Shrinking Circles: Adaptation to Increased Curvature Gain in Redirected Walking

LoCoMoTe - A Framework for Classification of Natural Locomotion in VR by Task, Technique and Modality

Virtual reality (VR) research has provided overviews of locomotion techniques, how they work, their strengths and overall user experience. Considerable research has investigated new methodologies, particularly machine learning to develop redirection algorithms. To best support the development of redirection algorithms through machine learning, we must understand how best to replicate human navigation and behaviour in VR, which can be supported by the accumulation of results produced through live-user experiments. However, it can be difficult to identify, select and compare relevant research without a pre-existing framework in an ever-growing research field. Therefore, this work aimed to facilitate the ongoing structuring and comparison of the VR-based natural walking literature by providing a standardised framework for researchers to utilise. We applied thematic analysis to study methodology descriptions from 140 VR-based papers that contained live-user experiments. From this analysis, we developed the LoCoMoTe framework with three themes: navigational decisions, technique implementation, and modalities. The LoCoMoTe framework provides a standardised approach to structuring and comparing experimental conditions. The framework should be continually updated to categorise and systematise knowledge and aid in identifying research gaps and discussions.

Redirected Walking for Exploring Immersive Virtual Spaces With HMD: A Comprehensive Review and Recent Advances

Real walking techniques can provide the user with a more natural, highly immersive walking experience compared to the experience of other locomotion techniques. In contrast to the direct mapping between the virtual space and an equal-sized physical space that can be simply realized, the nonequivalent mapping that enables the user to explore a large virtual space by real walking within a confined physical space is complex. To address this issue, the redirected walking (RDW) technique is proposed by many works to adjust the user's virtual and physical movements based on some redirection manipulations. In this manner, subtle or overt motion deviations can be injected between the user's virtual and physical movements, allowing the user to undertake real walking in large virtual spaces by using different redirection controller methods. In this paper, we present a brief review to describe major concepts and methodologies in the field of redirected walking. First, we provide the fundamentals and basic criteria of RDW, and then we describe the redirection manipulations that can be applied to adjust the user's movements during virtual exploration. Furthermore, we clarify the redirection controller methods that properly adopt strategies for combining different redirection manipulations and present a classification of these methods by several categories. Finally, we summarize several experimental metrics to evaluate the performance of redirection controller methods and discuss current challenges and future work. Our study systematically classifies the relevant theories, concepts, and methods of RDW, and provides assistance to the newcomers in understanding and implementing the RDW technique.

Redirected Walking using Continuous Curvature Manipulation

In this paper, we propose a novel redirected walking (RDW) technique that applies dynamic bending and curvature gains so that users perceive less discomfort than existing techniques that apply constant gains. Humans are less likely to notice continuous changes than those that are sudden. Therefore, instead of applying constant bending or curvature gains to users, we propose a dynamic method that continuously changes the gains. We conduct experiments to investigate the effect of dynamic gains in bending and curvature manipulation with regards to discomfort. The experimental results show that the proposed method significantly suppresses discomfort by up to 16 and 9% for bending and curvature manipulations, respectively.

Understanding, Modeling and Simulating Unintended Positional Drift during Repetitive Steering Navigation Tasks in Virtual Reality

Virtual steering techniques enable users to navigate in larger Virtual Environments (VEs) than the physical workspace available. Even though these techniques do not require physical movement of the users (e.g. using a joystick and the head orientation to steer towards a virtual direction), recent work observed that users might unintentionally move in the physical workspace while navigating, resulting in Unintended Positional Drift (UPD). This phenomenon can be a safety issue since users may unintentionally reach the physical boundaries of the workspace while using a steering technique. In this context, as a necessary first step to improve the design of navigation techniques minimizing the UPD, this paper aims at analyzing and modeling the UPD during a virtual navigation task. In particular, we characterize and analyze the UPD for a dataset containing the positions and orientations of eighteen users performing a virtual slalom task using virtual steering techniques. Participants wore a head-mounted display and had to follow three different sinusoidal-like trajectories (with low, medium and high curvature) using a torso-steering navigation technique. We analyzed the performed motions and proposed two UPD models: the first based on a linear regression analysis and the second based on a Gaussian Mixture Model (GMM) analysis. Then, we assessed both models through a simulation-based evaluation where we reproduced the same navigation task using virtual agents. Our results indicate the feasibility of using simulation-based evaluations to study UPD. The paper concludes with a discussion of potential applications of the results in order to gain a better understanding of UPD during steering and therefore improve the design of navigation techniques by compensating for UPD.

Controlling Teleportation-Based Locomotion in Virtual Reality with Hand Gestures: A Comparative Evaluation of Two-Handed and One-Handed Techniques

Virtual Reality (VR) technology offers users the possibility to immerse and freely navigate through virtual worlds. An important component for achieving a high degree of immersion in VR is locomotion. Often discussed in the literature, a natural and effective way of controlling locomotion is still a general problem which needs to be solved. Recently, VR headset manufacturers have been integrating more sensors, allowing hand or eye tracking without any additional required equipment. This enables a wide range of application scenarios with natural freehand interaction techniques where no additional hardware is required. This paper focuses on techniques to control teleportation-based locomotion with hand gestures, where users are able to move around in VR using their hands only. With the help of a comprehensive study involving 21 participants, four different techniques are evaluated. The effectiveness and efficiency as well as user preferences of the presented techniques are determined. Two two-handed and two one-handed techniques are evaluated, revealing that it is possible to move comfortable and effectively through virtual worlds with a single hand only.

The Security-Utility Trade-off for Iris Authentication and Eye Animation for Social Virtual Avatars

The gaze behavior of virtual avatars is critical to social presence and perceived eye contact during social interactions in Virtual Reality. Virtual Reality headsets are being designed with integrated eye tracking to enable compelling virtual social interactions. This paper shows that the near infra-red cameras used in eye tracking capture eye images that contain iris patterns of the user. Because iris patterns are a gold standard biometric, the current technology places the user's biometric identity at risk. Our first contribution is an optical defocus based hardware solution to remove the iris biometric from the stream of eye tracking images. We characterize the performance of this solution with different internal parameters. Our second contribution is a psychophysical experiment with a same-different task that investigates the sensitivity of users to a virtual avatar's eye movements when this solution is applied. By deriving detection threshold values, our findings provide a range of defocus parameters where the change in eye movements would go unnoticed in a conversational setting. Our third contribution is a perceptual study to determine the impact of defocus parameters on the perceived eye contact, attentiveness, naturalness, and truthfulness of the avatar. Thus, if a user wishes to protect their iris biometric, our approach provides a solution that balances biometric protection while preventing their conversation partner from perceiving a difference in the user's virtual avatar. This work is the first to develop secure eye tracking configurations for VR/AR/XR applications and motivates future work in the area.

Mind the Gap: The Underrepresentation of Female Participants and Authors in Virtual Reality Research

A common goal of human-subject experiments in virtual reality (VR) research is evaluating VR hardware and software for use by the general public. A core principle of human-subject research is that the sample included in a given study should be representative of the target population; otherwise, the conclusions drawn from the findings may be biased and may not generalize to the population of interest. In order to assess whether characteristics of participants in VR research are representative of the general public, we investigated participant demographic characteristics from human-subject experiments in the Proceedings of the IEEE Virtual Reality Conferences from 2015-2019. We also assessed the representation of female authors. In the 325 eligible manuscripts, which presented results from 365 human-subject experiments, we found evidence of significant underrepresentation of women as both participants and authors. To investigate whether this underrepresentation may bias researchers' findings, we then conducted a meta-analysis and meta-regression to assess whether demographic characteristics of study participants were associated with a common outcome evaluated in VR research: the change in simulator sickness following head-mounted display VR exposure. As expected, participants in VR studies using HMDs experienced small but significant increases in simulator sickness. However, across the included studies, the change in simulator sickness was systematically associated with the proportion of female participants. We discuss the negative implications of conducting experiments on non-representative samples and provide methodological recommendations for mitigating bias in future VR research.