Document Detail


Tuning Self-Motion Perception in Virtual Reality with Visual Illusions.
MedLine Citation:
PMID:  22084144     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Motion perception in immersive virtual environments significantly differs from the real world. For example, previous work has shown that users tend to underestimate travel distances in virtual environments (VEs). As a solution to this problem, researchers proposed to scale the mapped virtual camera motion relative to the tracked real-world movement of a user until real and virtual motion are perceived as equal, i.e., real-world movements could be mapped with a larger gain to the VE in order to compensate for the underestimation. However, introducing discrepancies between real and virtual motion can become a problem, in particular, due to misalignments of both worlds and distorted space cognition. In this article we describe a different approach that introduces apparent self-motion illusions by manipulating optic flow fields during movements in VEs. These manipulations can affect self-motion perception in VEs, but omit a quantitative discrepancy between real and virtual motions. In particular, we consider to which regions of the virtual view these apparent self-motion illusions can be applied, i.e., the ground plane or peripheral vision. Therefore, we introduce four illusions and show in experiments that optic flow manipulation can significantly affect users' self-motion judgments. Furthermore, we show that with such manipulations of optic flow fields the underestimation of travel distances can be compensated.
Authors:
Gerd Bruder; Frank Steinicke; Phil Wieland; Markus Lappe
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-11-8
Journal Detail:
Title:  IEEE transactions on visualization and computer graphics     Volume:  -     ISSN:  1077-2626     ISO Abbreviation:  -     Publication Date:  2011 Nov 
Date Detail:
Created Date:  2011-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9891704     Medline TA:  IEEE Trans Vis Comput Graph     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
University of Würzburg, Würzburg.
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