Extracting Features from 3D Unstructured Meshes for Interactive Visualization

This paper describes techniques, based on the extraction of geometric features, for facilitating the visualization and interactive manipulation of the typically very large and dense threedimensional unstructured grids used in aerodynamics calculations. We discuss the difficulties that scientists currently face in efficiently and effectively displaying these meshes and propose methods for using geometric feature lines to clearly and concisely indicate the essential structural detail of the model while eliminating much of the unnecessary visual clutter. We describe the perceptual importance of specific viewpoint-dependent and view-independent features, discuss the practical implementation of simple but effective algorithms for identifying these features (taking into consideration both local and global criteria), and demonstrate the performance of each proposed technique on various types of data sets. y This research was supported by the National Aeronautics and Space Administration unde..

NaviFields: relevance fields for adaptive VR navigation

Virtual Reality allow users to explore virtual environments naturally, by moving their head and body. However, the size of the environments they can explore is limited by real world constraints, such as the tracking technology or the physical space available. Existing techniques removing these limitations often break the metaphor of natural navigation in VR (e.g. steering techniques), involve control commands (e.g., teleporting) or hinder precise navigation (e.g., scaling user's displacements). This paper proposes NaviFields, which quantify the requirements for precise navigation of each point of the environment, allowing natural navigation within relevant areas, while scaling users' displacements when travelling across non-relevant spaces. This expands the size of the navigable space, retains the natural navigation metaphor and still allows for areas with precise control of the virtual head. We present a formal description of our NaviFields technique, which we compared against two alternative solutions (i.e., homogeneous scaling and natural navigation). Our results demonstrate our ability to cover larger spaces, introduce minimal disruption when travelling across bigger distances and improve very significantly the precise control of the viewpoint inside relevant areas

A Multisensory Approach to Virtual Reality Stress Reduction

Forest bathing is a nature immersion practice that reduces stress, restores mental resources, and has a wide variety of use cases in the treatment of mental illnesses. Since many people who need the benefits of forest bathing have little access to nature, virtual reality (VR) is being explored as a tool for delivering accessible immersive nature experiences via virtual nature environments (VNE's). Research on VNE's mainly utilizes the audiovisual capabilities of VR, but since forest bathing is a fully multisensory experience, further investigations into the integration of other sensory technologies, namely smell and temperature, are essential for the future of VNE research.Comment: 5 pages, 2 figure

Investigating the Correlation Between Presence and Reaction Time in Mixed Reality

Measuring presence is critical to improving user involvement and performance in Mixed Reality (MR). \emph{Presence}, a crucial aspect of MR, is traditionally gauged using subjective questionnaires, leading to a lack of time-varying responses and susceptibility to user bias. Inspired by the existing literature on the relationship between presence and human performance, the proposed methodology systematically measures a user's reaction time to a visual stimulus as they interact within a manipulated MR environment. We explore the user reaction time as a quantity that can be easily measured using the systemic tools available in modern MR devices. We conducted an exploratory study (N=40) with two experiments designed to alter the users' sense of presence by manipulating \emph{place illusion} and \emph{plausibility illusion}. We found a significant correlation between presence scores and reaction times with a correlation coefficient -0.65, suggesting that users with a higher sense of presence responded more swiftly to stimuli. We develop a model that estimates a user's presence level using the reaction time values with high accuracy of up to 80\%. While our study suggests that reaction time can be used as a measure of presence, further investigation is needed to improve the accuracy of the model

Visual assistance may impede sensorimotor learning during gamified rehabilitation exercises

Regular exercise is critical to post-stroke recovery, but can be frustrating and difficult for patients with limited motor capabilities. Robotic assistance devices are being used to support this process, but due to cost and accessibility concerns some researchers have drawn inspiration from virtual reality and proposed the use of what we call “visual-only assistance”, in which a patient’s physical movements are mapped into game-oriented visual feedback modified towards greater success in the gameplay objectives. Our concern is that the motivational benefits it provides may come at the cost of reduced sensorimotor learning, which could ultimately be counterproductive to the recovery process. To explore these concerns, we conducted a between-subjects study with 24 participants to examine how two types of visual-only assistance affect short-term proprioceptive skill learning in a motor training game involving airplane steering with wrist rotation. One group experienced “attractor assistance”, in which the airplane was continuously displaced toward an ideal position and orientation. The other experienced “tunnel assistance”, in which direct user control was maintained unless straying too far, triggering an invisible barrier. We hypothesized that motor learning would be more impeded with attractor assistance due to the constant mapping variation between physical movements and visual feedback, but our experiment found that motor learning did not materialize in either condition, suggesting that substituting intermittent visual assistance for constant visual assistance is insufficient to guarantee superior motor learning outcomes and that, pending further investigation, the use of visual assistance for proprioceptive training should continue to be regarded with caution

Gaze prediction using machine learning for dynamic stereo manipulation in games.

Comfortable, high-quality 3D stereo viewing is becoming a requirement for interactive applications today. Previous research shows that manipulating disparity can alleviate some of the discomfort caused by 3D stereo, but it is best to do this locally, around the object the user is gazing at. The main challenge is thus to develop a gaze predictor in the demanding context of real-time, heavily task-oriented applications such as games. Our key observation is that player actions are highly correlated with the present state of a game, encoded by game variables. Based on this, we train a classifier to learn these correlations using an eye-tracker which provides the ground-truth object being looked at. The classifier is used at runtime to predict object category - and thus gaze - during game play, based on the current state of game variables. We use this prediction to propose a dynamic disparity manipulation method, which provides rich and comfortable depth. We evaluate the quality of our gaze predictor numerically and experimentally, showing that it predicts gaze more accurately than previous approaches. A subjective rating study demonstrates that our localized disparity manipulation is preferred over previous methods

Illustrating Surface Shape in Volume Data via Principal Direction-Driven 3D Line Integral Convolution

The three-dimensional shape and relative depth of a smoothly curving layered transparent surface may be communicated particularly effectively when the surface is artistically enhanced with sparsely distributed opaque detail. This paper describes how the set of principal directions and principal curvatures specified by local geometric operators can be understood to define a natural "flow " over the surface of an object, and can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape information in a perceptually intuitive way. The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures. By advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate

Extracting features from 3D unstructured meshes for interactive visualization

This paper describes techniques, based on the extraction of geometric features, for facilitating the visualization and interactive manipulation of the typically very large and dense three-dimensional unstructured grids used in aerodynamics calculations. We discuss the difficulties that scientists currently face in efficiently and effectively dis-playing these meshes and propose methods for using geometric feature lines to clearly and concisely indicate the essential structural detail of the model while eliminating much of the unnecessary visual clutter. We describe the perceptual importance of specific viewpoint-dependent and view-independent features, discuss the practical implementation of simple but effective algorithms for identify-ing these features (taking into consideration both local and global criteria), and demonstrate the performance of each proposed technique on various types of data sets