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虚拟现实中的显著性:人们如何探索虚拟环境?

Saliency in VR: How Do People Explore Virtual Environments?

出版信息

IEEE Trans Vis Comput Graph. 2018 Apr;24(4):1633-1642. doi: 10.1109/TVCG.2018.2793599.

Abstract

Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention. Whereas a body of recent work has focused on modeling saliency in desktop viewing conditions, VR is very different from these conditions in that viewing behavior is governed by stereoscopic vision and by the complex interaction of head orientation, gaze, and other kinematic constraints. To further our understanding of viewing behavior and saliency in VR, we capture and analyze gaze and head orientation data of 169 users exploring stereoscopic, static omni-directional panoramas, for a total of 1980 head and gaze trajectories for three different viewing conditions. We provide a thorough analysis of our data, which leads to several important insights, such as the existence of a particular fixation bias, which we then use to adapt existing saliency predictors to immersive VR conditions. In addition, we explore other applications of our data and analysis, including automatic alignment of VR video cuts, panorama thumbnails, panorama video synopsis, and saliency-basedcompression.

摘要

理解人们如何探索沉浸式虚拟环境对于许多应用至关重要,例如设计虚拟现实 (VR) 内容、开发新的压缩算法,或学习显著性或视觉注意的计算模型。虽然最近有大量的研究集中在模拟桌面观察条件下的显著性,但 VR 与这些条件非常不同,因为观察行为受到立体视觉和头部方向、注视以及其他运动学约束的复杂交互的影响。为了进一步了解 VR 中的观察行为和显著性,我们捕获和分析了 169 位用户在探索立体、静态全向全景时的注视和头部方向数据,对于三种不同的观察条件,共获得了 1980 个头和注视轨迹。我们对数据进行了全面分析,得出了几个重要的见解,例如存在特定的注视偏差,然后我们使用该偏差来适应现有的显著性预测器到沉浸式 VR 条件。此外,我们还探索了数据和分析的其他应用,包括 VR 视频剪辑、全景缩略图、全景视频概要和基于显著性的压缩的自动对齐。

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