Full UHD 360-Degree Video Dataset and Modeling of Rate-Distortion Characteristics and Head Movement Navigation

Abstract

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.