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Conference proceeding
Using videos derived from simulations to support the analysis of spatial awareness in synthetic vision displays
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, v 6, pp 5203-5208
01 Jan 2006
Abstract
The evaluation of human-centered systems can be performed using a variety of different methodologies. This paper describes a human-centered systems' evaluation methodology where participants watch 5-second non-interactive videos of a system in operation before supplying judgments and subjective measures based on the information conveyed in the videos. This methodology was used to evaluate the ability of different textures and fields of view to convey spatial awareness in synthetic vision systems (SVS) displays. It produced significant results for both judgment based and subjective measures. This method is compared to other methods commonly used to evaluate SVS displays based on cost, the amount of experimental time required, experimental flexibility, and the type of data provided.
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1 citations in Scopus
Details
- Title
- Using videos derived from simulations to support the analysis of spatial awareness in synthetic vision displays
- Creators
- Matthew L. Bolton - University of VirginiaEllen J. Bass - University of VirginiaJames R. Comstock - Langley Research CenterIEEE
- Publication Details
- 2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, v 6, pp 5203-5208
- Series
- IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- NIA; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA) NASA; National Aeronautics & Space Administration (NASA) UVA-03-01; 4817-UV / Systems - Rising Star
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000248078505132
- Scopus ID
- 2-s2.0-34548133700
- Other Identifier
- 991019292227404721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics