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- W3202211207 abstract "Virtual reality (VR) is a powerful modern medium. The advent of low-cost head-mounted display (HMD) devices made this technology accessible at large and featured VR with possibilities to monitor interactions and user’s motion. However, due to lack of real-time feedback mechanism at present, the level of intelligence for virtual environments is still not sufficient to assist the experience and make group or individual assessments towards VR based applications. In this paper, we present our findings related to the problem of real-time feedback that focus on behavioral data by employing the novel feedback mechanism. Virtual-world coordinates, motions and interactions are tracked and captured in real-time while the user experiences particular application. Captured data is investigated to target the issue of complementing VR applications with features derived from real-time behavioral analysis. In our experiment, we also use collected data and provide a methodology to predict virtual-location by the nonlinear auto-regressive neural network with exogenous inputs (NARX). Results suggest employed neural network model is suitable for performing prediction which can be used to obtain a virtual environment with adaptive intelligence." @default.
- W3202211207 created "2021-10-11" @default.
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- W3202211207 date "2021-01-01" @default.
- W3202211207 modified "2023-09-24" @default.
- W3202211207 title "Intelligent Virtual Environments with Assessment of User Experiences" @default.
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- W3202211207 doi "https://doi.org/10.1007/978-3-030-87986-0_41" @default.
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