2,685 research outputs found
MetaSpace II: Object and full-body tracking for interaction and navigation in social VR
MetaSpace II (MS2) is a social Virtual Reality (VR) system where multiple
users can not only see and hear but also interact with each other, grasp and
manipulate objects, walk around in space, and get tactile feedback. MS2 allows
walking in physical space by tracking each user's skeleton in real-time and
allows users to feel by employing passive haptics i.e., when users touch or
manipulate an object in the virtual world, they simultaneously also touch or
manipulate a corresponding object in the physical world. To enable these
elements in VR, MS2 creates a correspondence in spatial layout and object
placement by building the virtual world on top of a 3D scan of the real world.
Through the association between the real and virtual world, users are able to
walk freely while wearing a head-mounted device, avoid obstacles like walls and
furniture, and interact with people and objects. Most current virtual reality
(VR) environments are designed for a single user experience where interactions
with virtual objects are mediated by hand-held input devices or hand gestures.
Additionally, users are only shown a representation of their hands in VR
floating in front of the camera as seen from a first person perspective. We
believe, representing each user as a full-body avatar that is controlled by
natural movements of the person in the real world (see Figure 1d), can greatly
enhance believability and a user's sense immersion in VR.Comment: 10 pages, 9 figures. Video:
http://living.media.mit.edu/projects/metaspace-ii
Real walking in virtual environments for factory planning and evaluation
Nowadays, buildings or production facilities are designed using specialized design software and building information modeling tools help to evaluate the resulting virtual mock-up. However, with current, primarily desktop based tools it is hard to evaluate human factors of such a design, for instance spatial constraints for workforces. This paper presents a new tool for factory planning and evaluation based on virtual reality that allows designers, planning experts, and workforces to walk naturally and freely within a virtual factory. Therefore, designs can be checked as if they were real before anything is built.ISSN:2212-827
ARC: Alignment-based Redirection Controller for Redirected Walking in Complex Environments
We present a novel redirected walking controller based on alignment that
allows the user to explore large and complex virtual environments, while
minimizing the number of collisions with obstacles in the physical environment.
Our alignment-based redirection controller, ARC, steers the user such that
their proximity to obstacles in the physical environment matches the proximity
to obstacles in the virtual environment as closely as possible. To quantify a
controller's performance in complex environments, we introduce a new metric,
Complexity Ratio (CR), to measure the relative environment complexity and
characterize the difference in navigational complexity between the physical and
virtual environments. Through extensive simulation-based experiments, we show
that ARC significantly outperforms current state-of-the-art controllers in its
ability to steer the user on a collision-free path. We also show through
quantitative and qualitative measures of performance that our controller is
robust in complex environments with many obstacles. Our method is applicable to
arbitrary environments and operates without any user input or parameter
tweaking, aside from the layout of the environments. We have implemented our
algorithm on the Oculus Quest head-mounted display and evaluated its
performance in environments with varying complexity. Our project website is
available at https://gamma.umd.edu/arc/
Monte-Carlo Redirected Walking: Gain Selection Through Simulated Walks
We present Monte-Carlo Redirected Walking (MCRDW), a gain selection algorithm for redirected walking. MCRDW applies the Monte-Carlo method to redirected walking by simulating a large number of simple virtual walks, then inversely applying redirection to the virtual paths. Different gain levels and directions are applied, producing differing physical paths. Each physical path is scored and the results used to select the best gain level and direction. We provide a simple example implementation and a simulation-based study for validation. In our study, when compared with the next best technique, MCRDW reduced incidence of boundary collisions by over 50% while reducing total rotation and position gain
Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering
Redirected walking is a Virtual Reality(VR) locomotion technique which
enables users to navigate virtual environments (VEs) that are spatially larger
than the available physical tracked space. In this work we present a novel
technique for redirected walking in VR based on the psychological phenomenon of
inattentional blindness. Based on the user's visual fixation points we divide
the user's view into zones. Spatially-varying rotations are applied according
to the zone's importance and are rendered using foveated rendering. Our
technique is real-time and applicable to small and large physical spaces.
Furthermore, the proposed technique does not require the use of stimulated
saccades but rather takes advantage of naturally occurring saccades and blinks
for a complete refresh of the framebuffer. We performed extensive testing and
present the analysis of the results of three user studies conducted for the
evaluation
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
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