Target and steering-based techniques are two common approaches to travel in consumer VR applications. In this paper, we present two within-subject studies that employ a prior dual-task methodology to evaluate and compare the cognitive loads, travel performances, and simulator sickness of three common target-based travel techniques and three common steering-based travel techniques. We also present visual meta-analyses comparing our results to prior results using the same dual-task methodology. Based on our results and meta-analyses, we present several design suggestions for travel techniques based on various aspects of user experiences.

Walking metaphors have been extensively researched for travel in virtual reality (VR) applications. However, only a few walking metaphors are feasible for most consumer VR systems. In this paper, we present a study that compares three of these suitable metaphors: Scaled Walking, Human Joystick, and Walking-In-Place. Our study empirically assesses the cognitive loads and travel performances of these three walking metaphors by employing a novel dual-task methodology. We also evaluated their effects on simulator sickness, presence, and perceived usability. The results of our study indicate that Scaled Walking afforded significantly better travel performances and perceived usability than Human Joystick and Walking-In-Place. Our results also indicate that Walking-In-Place required the worst cognitive loads and that Human Joystick induced the worst simulator sickness. Given these results, we discuss the implications of using a high-fidelity, full-gait walking metaphor.

With the increasing accessibility of the mobile head-mounted displays (HMDs), mobile virtual reality (VR) systems are finding applications in various areas. However, mobile HMDs are highly constrained with limited graphics processing units (GPUs) and low processing power and onboard memory. Hence, VR developers must be cognizant of the number of polygons contained within their virtual environments to avoid rendering at low frame rates and inducing simulator sickness. The most robust and rapid approach to keeping the overall number of polygons low is to use mesh simplification algorithms to create low-poly versions of pre-existing, high-poly models. Unfortunately, most existing mesh simplification algorithms cannot adequately handle meshes with lots of boundaries or nonmanifold meshes, which are common attributes of many 3D models. In this article, we present QEM 4VR , a high-fidelity mesh simplification algorithm specifically designed for VR. This algorithm addresses the deficiencies of prior quadric error metric (QEM) approaches by leveraging the insight that the most relevant boundary edges lie along curvatures while linear boundary edges can be collapsed. Additionally, our algorithm preserves key surface properties, such as normals, texture coordinates, colors, and materials, as it preprocesses 3D models and generates their low-poly approximations offline. We evaluated the effectiveness of our QEM 4VR algorithm by comparing its simplified-mesh results to those of prior QEM variations in terms of geometric approximation error, texture error, progressive approximation errors, frame rate impact, and perceptual quality measures. We found that QEM 4VR consistently yielded simplified meshes with less geometric approximation error and texture error than the prior QEM variations. It afforded better frame rates than QEM variations with boundary preservation constraints that create unnecessary lower bounds on overall polygon count reduction. Our evaluation revealed that QEM 4VR did not fair well in terms of existing perceptual distance measurements, but human-based inspections demonstrate that these algorithmic measurements are not suitable substitutes for actual human perception. In turn, we present a user-based methodology for evaluating the perceptual qualities of mesh simplification algorithms.

With the increasing accessibility of the mobile head-mounted displays (HMDs), mobile virtual reality (VR) systems are finding applications in various areas. However, mobile HMDs are highly constrained with limited graphics processing units (GPUs), low processing power and onboard memory. Hence, VR developers must be cognizant of the number of polygons contained within their virtual environments to avoid rendering at low frame rates and inducing simulator sickness. The most robust and rapid approach to keeping the overall number of polygons low is to use mesh simplification algorithms to create low-poly versions of preexisting, high-poly models. Unfortunately, most existing mesh simplification algorithms cannot adequately handle meshes with lots of boundaries or non-manifold meshes, which are common attributes of 3D models made with computer-aided design tools.; [email protected] this paper, we present a high-fidelity mesh simplification algorithm specifically designed for VR. This new algorithm, QEM4VR, addresses the deficiencies of prior quadric error metric (QEM) approaches by leveraging the insight that the most relevant boundary edges lie along curvatures while linear boundary edges can be collapsed. Additionally, our QEM4VR algorithm preserves key surface properties, such as normals, texture coordinates, colors, and materials. It pre-processes the 3D models and generate their low-poly approximations offline. We used six publicly available, high-poly models, with and without textures to compare the accuracy and fidelity of our QEM4VR algorithm to previous QEM variations. We also performed a frame rate analysis with original high-poly models and low-poly models obtained using QEM4VR and previous QEM variations. Our results indicate that QEM4VR creates low-poly, high-fidelity virtual environments for VR applications on devices that are constrained by the low number of polygons they can work with.