Adaptive streaming of 3D content for web-based virtual reality: an open-source prototype including several metrics and strategies

Abstract

Virtual reality is a new technology that has been developing a lot during the last decade. With autonomous head-mounted displays appearing on the market, new uses and needs have been created. The 3D content displayed by those devices can now be stored on distant servers rather than directly in the device's memory. In such networked immersive experiences, the 3D environment has to be streamed in real-time to the headset. In that context, several recent papers proposed utility metrics and selection strategies to schedule the streaming of the different objects composing the 3D environment, in order to minimize the latency and to optimize the quality of what is being visualized by the user at each moment. However, these proposed frameworks are hardly comparable since they operate on different systems and data. Therefore, we hereby propose an open-source DASH-based web framework for adaptive streaming of 3D content in a 6 Degrees of Freedom (DoFs) scenario. Our framework integrates several strategies and utility metrics from the state of the art, as well as several relevant features: 3D graphics compression, levels of details and the use of a visual quality index. We used our software to demonstrate the relevance of those tools and provide useful hints for the community for the further improvements of 3D streaming systems.