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Strategies and Metrics for Evaluating the Quality of Experience in Virtual Reality Applications

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Human Systems Engineering and Design (IHSED 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 876))

Abstract

The development of virtual reality makes it possible to apply the technology in many fields, but the experience of users received limited attention. Quality of experience (QoE) is an evaluation metrics can be used to evaluate applications and services from the perspective of users. By an intensive analysis of the literature about user experience models and QoE related projects, three strategies for QoE evaluation were put forward: emphasizing user needs, emphasizing system characteristics and emphasizing emotional experience. As an example, a set of metrics for the evaluation of astronaut virtual training system (AVTS) are designed under the guidance of the strategies, which consists of five first-level indicators and ten second-level indicators and can be used to quantify the quality of experience of the astronaut virtual training system.

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Acknowledgement

This work was supported by the Foundation of National Key Laboratory of Human Factors Engineering, Grant NO. SYFD160051802.

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Authors and Affiliations

  1. National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China

    Xiangjie Kong & Yuqing Liu

Authors
  1. Xiangjie Kong
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  2. Yuqing Liu
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Corresponding author

Correspondence to Xiangjie Kong .

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Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

  2. University of Central Florida, Orlando, FL, USA

    Waldemar Karwowski

  3. Université de Reims Champagne-Ardenne, Reims, France

    Redha Taiar

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Kong, X., Liu, Y. (2019). Strategies and Metrics for Evaluating the Quality of Experience in Virtual Reality Applications. In: Ahram, T., Karwowski, W., Taiar, R. (eds) Human Systems Engineering and Design. IHSED 2018. Advances in Intelligent Systems and Computing, vol 876. Springer, Cham. https://doi.org/10.1007/978-3-030-02053-8_48

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