DocumentCode :
921703
Title :
Development and Evaluation of a Bayesian Low-Vision Navigation Aid
Author :
Stankiewicz, Brian J. ; Cassandra, Anthony R. ; McCabe, Matthew R. ; Weathers, William
Author_Institution :
Texas Univ., Austin
Volume :
37
Issue :
6
fYear :
2007
Firstpage :
970
Lastpage :
983
Abstract :
Way finding in unfamiliar environments can pose a challenge to anyone but can be particularly challenging to someone who has some sort of visual loss. In this paper, we describe an indoor navigation aid that uses Bayesian statistics to localize and guide an individual from an unspecified location within a building to a specific destination. We also present three studies investigating the efficacy of this system as a low-vision navigation aid. Two studies were conducted in virtual indoor buildings using desktop virtual reality (VR) and one study was conducted in a real building. All three studies investigated navigation performance with versus without the navigation aid. In all three studies, subjects traveled a shorter distance with the navigation aid than without it. In the VR studies, the navigation aid actually improved performance over navigating with normal vision.
Keywords :
Bayes methods; computerised navigation; handicapped aids; virtual reality; Bayesian low-vision navigation aid; Bayesian statistics; desktop virtual reality; indoor navigation aid; virtual indoor buildings; Bayesian methods; Diabetes; Handicapped aids; Human factors; Lenses; Navigation; Optical materials; Psychology; Statistics; Virtual reality; Belief maintenance; handicapped aids; human factors; navigation;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4427
Type :
jour
DOI :
10.1109/TSMCA.2007.897713
Filename :
4342805
Link To Document :
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