Full UHD 360-Degree Video Dataset and Modeling of Rate-Distortion Characteristics and Head Movement Navigation
Full UHD 360-Degree Video Dataset and Modeling of Rate-Distortion Characteristics and Head Movement Navigation
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DOI：
10.1145/3458305.3478447
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发表时间：
2021-06
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影响因子：
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通讯作者：
Jacob Chakareski;Ridvan Aksu;Viswanathan Swaminathan;M. Zink
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作者：
Jacob Chakareski;Ridvan Aksu;Viswanathan Swaminathan;M. Zink
我们研究了全超高清（UHD） 360°视频的率失真（R-D）特性，并捕获了虚拟现实（VR）头显的相应头部运动导航数据。我们使用导航数据来分析用户如何在360°环视全景中探索这些内容，并建立相关的统计模型。开发的R-D特征和建模捕获了内容在多个尺度上的时空编码效率，并可用于在关键用例中实现更高的操作效率。对下一代沉浸式媒体的高质量期望需要理解全UHD 360°视频的这些内在导航和内容特征。
We investigate the rate-distortion (R-D) characteristics of full ultra-high definition (UHD) 360° videos and capture corresponding head movement navigation data of virtual reality (VR) headsets. We use the navigation data to analyze how users explore the 360° look-around panorama for such content and formulate related statistical models. The developed R-D characteristics and modeling capture the spatiotemporal encoding efficiency of the content at multiple scales and can be exploited to enable higher operational efficiency in key use cases. The high quality expectations for next generation immersive media necessitate the understanding of these intrinsic navigation and content characteristics of full UHD 360° videos.