Title
Impossible Spaces: Maximizing Natural Walking in Virtual Environments with Self-Overlapping Architecture
Abstract
Walking is only possible within immersive virtual environments that fit inside the boundaries of the user’s physical workspace. To reduce the severity of the restrictions imposed by limited physical area, we introduce "impossible spaces," a new design mechanic for virtual environments that wish to maximize the size of the virtual environment that can be explored with natural locomotion. Such environments make use of self–overlapping architectural layouts, effectively compressing comparatively large interior environments into smaller physical areas. We conducted two formal user studies to explore the perception and experience of impossible spaces. In the first experiment, we showed that reasonably small virtual rooms may overlap by as much as 56% before users begin to detect that they are in an impossible space, and that the larger virtual rooms that expanded to maximally fill our available 9.14m x 9.14m workspace may overlap by up to 31%. Our results also demonstrate that users perceive distances to objects in adjacent overlapping rooms as if the overall space was uncompressed, even at overlap levels that were overtly noticeable. In our second experiment, we combined several well–known redirection techniques to string together a chain of impossible spaces in an expansive outdoor scene. We then conducted an exploratory analysis of users’ verbal feedback during exploration, which indicated that impossible spaces provide an even more powerful illusion when users are naive to the manipulation.
Year
DOI
Venue
2012
10.1109/TVCG.2012.47
IEEE Trans. Vis. Comput. Graph.
Keywords
Field
DocType
gait analysis,layout,illusion,virtual reality,estimation,computer graphics,environment,feedback,young adult,perception,virtual environment,human computer interaction,space exploration
Illusion,Computer vision,Architecture,Virtual reality,Virtual machine,Computer science,Workspace,Space exploration,Immersion (virtual reality),Artificial intelligence,Multimedia,Perception
Journal
Volume
Issue
ISSN
18
4
1077-2626
Citations 
PageRank 
References 
47
1.67
23
Authors
5
Name
Order
Citations
PageRank
Evan A. Suma178067.37
Zachary Lipps2522.15
Samantha Finkelstein31137.51
David M. Krum442837.57
Mark Bolas588089.87