Understanding user navigation in immersive experience: an information-theoretic analysis
Understanding user navigation in immersive experience: an information-theoretic analysis
复制标题
了解沉浸式体验中的用户导航：信息论分析
DOI：
10.1145/3386293.3397115
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
L. Toni
中科院分区：
文献类型：
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作者：
Silvia Rossi;L. Toni
为了科普大带宽和低延迟的需求，虚拟现实（VR）系统正在转向以用户为中心的系统，其中编码，流媒体和可能的渲染都是针对最终用户的个性化。这些以用户为中心的VR系统的成功主要依赖于预测观众导航的能力。这激发了人们对研究VR体验中用户运动预测的极大关注。然而，这些工作中的大多数都缺乏VR场景中适当和详尽的行为分析，留下了许多未解决和未探索的关键行为问题：一些用户是否比其他用户更可预测？用户是否有自己的导航方式，这在多大程度上受到视频内容功能的影响？我们能量化用户导航的相似性吗？解决这些问题是理解VR中用户行为的关键一步，也是本文的总体目标。通过研究不同内容的VR轨迹和信息理论工具，我们的目标是为每个观众（单独分析观众-用户内分析）和众多观众（识别观众之间的共同模式-用户间分析）描述导航模式。对于每一个这些拟议的行为分析，我们描述了应用的指标和关键的意见，可以推断。
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.