Immersive Virtual Reality Model Preparation Framework: Towards a Fair and Standardized Performance Comparison
Bing Han, Fernanda L. Leite · Construction Research Congress 2020 · 2020
Immersive virtual reality (IVR) has begun to provide business value with sufficiently mature equipment and related software. The construction industry has shown interest in IVR due to its high-level visualization needs. However, the lack of fair performance comparisons among IVR and other cutting-edge competitors hampered the industry implementation of IVR. This paper filled the knowledge gap by developing a standardized model preparation framework for IVR performance research. The framework emphasized essential operations to realize the full potential of IVR. Researchers performed human-involved experiments in a design error detection task with thirteen participants. Researchers validated the framework by comparing user performance data before and after utilizing the proposed framework in the IVR environment. Results showed that the framework substantially mitigated simulator sickness, enhanced user performance by 87.21%, and decreased 58.17% invalid operations per minute when utilizing supporting functions. This paper provided a fair IVR environment for performance comparison with other state-of-the-art visualization technologies, and accordingly, the model preparation framework can contribute to a broad range of IVR performance research.