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    An Information-Theoretic Approach to the Cost-benefit Analysis of Visualization in Virtual Environments

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    Authors
    Chen, Min
    Gaither, Kelly
    John, Nigel W.
    McCann, Brian
    Affiliation
    University of Oxford; University of Texas at Austin; University of Chester
    Publication Date
    2018-08-20
    
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    Abstract
    Visualization and virtual environments (VEs) have been two interconnected parallel strands in visual computing for decades. Some VEs have been purposely developed for visualization applications, while many visualization applications are exemplary showcases in general-purpose VEs. Because of the development and operation costs of VEs, the majority of visualization applications in practice have yet to benefit from the capacity of VEs. In this paper, we examine this status quo from an information-theoretic perspective. Our objectives are to conduct cost-benefit analysis on typical VE systems (including augmented and mixed reality, theatre-based systems, and large powerwalls), to explain why some visualization applications benefit more from VEs than others, and to sketch out pathways for the future development of visualization applications in VEs. We support our theoretical propositions and analysis using theories and discoveries in the literature of cognitive sciences and the practical evidence reported in the literatures of visualization and VEs.
    Citation
    M. Chen, K. Gaither, N. W. John and B. Mccann, "An Information-Theoretic Approach to the Cost-benefit Analysis of Visualization in Virtual Environments," in IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 1, pp. 32-42, Jan. 2019. doi: 10.1109/TVCG.2018.2865025
    Publisher
    IEEE
    Journal
    IEEE Transactions on Visualization and Computer Graphics
    URI
    http://hdl.handle.net/10034/621411
    DOI
    10.1109/TVCG.2018.2865025
    Additional Links
    https://ieeexplore.ieee.org/abstract/document/8440821
    Type
    Article
    Language
    en
    Description
    © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    EISSN
    1941-0506
    ae974a485f413a2113503eed53cd6c53
    10.1109/TVCG.2018.2865025
    Scopus Count
    Collections
    Computer Science

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