Viewport-Driven Rate-Distortion Optimized 360{\deg} Video Streaming

The growing popularity of virtual and augmented reality communications and 360◦ video streaming is moving video communication systems into much more dynamic and resource-limited operating settings. The enormous data volume of 360◦ videos requires an efficient use of network bandwidth to maintain the desired quality of experience for the end user. To this end, we propose a framework for viewport-driven rate-distortion optimized 360◦ video streaming that integrates the user view navigation pattern and the spatiotemporal rate-distortion characteristics of the 360◦ video content to maximize the delivered user quality of experience for the given network/system resources. The framework comprises a methodology for constructing dynamic heat maps that capture the likelihood of navigating different spatial segments of a 360◦ video over time by the user, an analysis and characterization of its spatiotemporal rate-distortion characteristics that leverage preprocessed spatial tilling of the 360 ◦ view sphere, and an optimization problem formulation that characterizes the delivered user quality of experience given the user navigation patterns, 360◦ video encoding decisions, and the available system/network resources. Our experimental results demonstrate the advantages of our framework over the conventional approach of streaming a monolithic uniformlyencoded 360◦ video and a state-of-the-art reference method. Considerable video quality gains of 4 5 dB are demonstrated in the case of two popular 4K 360◦ videos.