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Understanding User Navigation in Immersive Experience: an Information-Theoretic analysis

Rossi, S; Toni, L; (2020) Understanding User Navigation in Immersive Experience: an Information-Theoretic analysis. In: MMVE '20: Proceedings of the 12th ACM International Workshop on Immersive Mixed and Virtual Environment Systems. (pp. pp. 19-24). ACM Green open access

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Abstract

To cope with the large bandwidth and low-latency requirements, Virtual Reality (VR) systems are steering toward user-centric systems in which coding, streaming, and possibly rendering are personalized to the final user. The success of these user-centric VR systems mainly relies on the ability to anticipate viewers navigation. This has motivated a large attention in studying the prediction of user's movements in a VR experience. However, most of these work lack of a proper and exhaustive behavioural analysis in a VR scenario, leaving many key-behavioural questions unsolved and unexplored: Can some users be more predictable than others? Do users have their own way of navigating and how much is this affected by the video content features? Can we quantify the similarity of users navigation? Answering these questions is a crucial step toward the understanding of user's behaviour in VR; and it is the overall goal of this paper. By studying VR trajectories across different contents and through information-theoretic tools, we aim at characterizing navigation patterns both for each single viewer (profiling individually viewers - intra-user analysis) and for a multitude of viewers (identifying common patterns among viewers - inter-user analysis). For each of these proposed behavioural analyses, we describe the applied metrics and key observations that can be extrapolated.

Type: Proceedings paper
Title: Understanding User Navigation in Immersive Experience: an Information-Theoretic analysis
Event: International Workshop on Immersive Mixed and Virtual Environment Systems
Dates: 08 June 2020 - 11 June 2020
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3386293.3397115
Publisher version: https://doi.org/10.1145/3386293.3397115
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10096514
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