Encoding, decoding, and rendering pipeline for multiview streaming and display in VR using VVC

Virtual reality (VR) head-mounted displays (HMDs) require high bitrates for immersive, high-quality visuals. Versatile Video Coding (VVC) significantly improves compression efficiency, making it ideal for VR multiview streaming and display. However, VR multiview streaming and display face two challenges: ultra-high bandwidth and ultra-low latency requirements for an optimal user experience. This paper presents an integrated, end-to-end pipeline to address these challenges, including (i) field of view (FOV)-based bitrate allocation, (ii) adaptive streaming for dynamic network conditions, and (iii) real-time decoding and rendering optimizations. We explore FOV-based bitrate allocation to prioritize user’s focus area and adaptive streaming algorithms to handle network fluctuations. For high-end devices like Vision Pro, we implement a software-based decoding and rendering approach with VVC, minimizing latency and improving rendering efficiency. This work presents a VVC-based pipeline for multiview streaming and display in VR, focusing on bitrate allocation, adaptive streaming, and real-time decoding and rendering optimizations.

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Publication Details

Published
2025-09-16
DOI
https://doi.org/10.1117/12.3067317
Primary Topic
Image and Video Quality Assessment
Type
article
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article

Encoding, decoding, and rendering pipeline for multiview streaming and display in VR using VVC

Xueshi Hou, Shan Liu
Image and Video Quality Assessment
article

Encoding, decoding, and rendering pipeline for multiview streaming and display in VR using VVC

Xueshi Hou, Shan Liu
article en

Abstract

Virtual reality (VR) head-mounted displays (HMDs) require high bitrates for immersive, high-quality visuals. Versatile Video Coding (VVC) significantly improves compression efficiency, making it ideal for VR multiview streaming and display. However, VR multiview streaming and display face two challenges: ultra-high bandwidth and ultra-low latency requirements for an optimal user experience. This paper presents an integrated, end-to-end pipeline to address these challenges, including (i) field of view (FOV)-based bitrate allocation, (ii) adaptive streaming for dynamic network conditions, and (iii) real-time decoding and rendering optimizations. We explore FOV-based bitrate allocation to prioritize user’s focus area and adaptive streaming algorithms to handle network fluctuations. For high-end devices like Vision Pro, we implement a software-based decoding and rendering approach with VVC, minimizing latency and improving rendering efficiency. This work presents a VVC-based pipeline for multiview streaming and display in VR, focusing on bitrate allocation, adaptive streaming, and real-time decoding and rendering optimizations.

Tencent (China) (CN)
Openalex Percentile: Top 75%
Image and Video Quality Assessment
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