VV-DASH: A Framework for Volumetric Video DASH Streaming

Hadi Heidarirad, Mea Wang

Abstract: With the increasing demand for immersive experiences, volumetric video has emerged as a critical technology, offering users six degrees of freedom (6DoF) to fully explore three-dimensional scenes. However, despite significant advancements, there remains a lack of a comprehensive and flexible adaptive streaming framework capable of delivering volumetric video over dynamic network conditions. To address this gap, we present VV-DASH, an end-to-end framework for adaptive volumetric video streaming over DASH (Dynamic Adaptive Streaming over HTTP). Our framework covers the entire streaming pipeline, from video source to video playback. We propose a codec-agnostic DASH Volumetric Video (DVV) segment format that consolidates compressed video content into DASH-ready segments. This segmentation improves achievable streaming throughput by 13.2%, effectively reduces bandwidth demand, and enhances the achievable streaming bitrate by up to 37.8%. In summary, VV-DASH provides a practical, high-performance framework for scalable and adaptive volumetric video streaming.