Paper Info
Title
Visualizing Natural Environments From Data In Virtual Reality: Combining Realism And Uncertainty
Abstract
Understanding complex scientific data visualizations in 2D can be challenging. Virtual Reality (VR) provides an alternative, combining realistic 3D representations with intuitive, natural interactions with data through embodied experiences. However, realistic 3D representations and associated immersive experiences are prone to misrepresentations as they are selectively representative and often leave little room for abstraction. This is particularly challenging for topics such as modeling natural environments where users value realism. We discuss the causes and categories of potential misrepresentations in VR with a particular focus on scientific visualization. We contextualize our discussion by presenting an application prototype that translates ecological model output data into a high-fidelity VR experience that allows users to walk through forests of the future. We also designed and implemented two methods to display uncertainties in high-fidelity VR environments: A multi-scenarios approach to provide users access to alternative scenarios, and a slide-and-show approach to view the environment within the confidence interval.
Year
DOI
Venue
2019
10.1109/VR.2019.8797996
2019 26TH IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES (VR)
Keywords
Field
DocType
Visualization, scientific visualization, virtual reality
Computer vision,Data visualization,Virtual reality,Visualization,Computer science,Embodied cognition,Human–computer interaction,Immersion (virtual reality),Human-centered computing,Artificial intelligence,Computer graphics,Scientific visualization
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Jiawei Huang121242.62
Melissa S. Lucash201.35
Mark B. Simpson300.34
Casey Helgeson400.34
Alexander Klippel548349.70