{"title":"NAVA: A Network-Adaptive View-Aware Volumetric Video Streaming Framework","authors":"Nguyen Long Quang;Truong Thu Huong;Duc Nguyen","doi":"10.1109/ACCESS.2025.3538802","DOIUrl":null,"url":null,"abstract":"Volumetric video is the emerging format for representing real-world dynamic objects such as humans in Extended Reality (XR) applications. However, real-time streaming of volumetric video to user devices is challenging due to the extremely high data rate and low latency requirements. This paper introduces NAVA, a novel network-adaptive view-aware volumetric video streaming framework for XR scenes consisting of multiple volumetric sequences. The proposed framework dynamically adapts the quality of individual volumetric sequences based on network conditions and the user’s viewpoint to optimize streaming performance under network constraints. In our framework, multiple versions with different quality of individual volumetric video are prepared and stored on the server in advance. The rate allocation problem is formulated as a optimization problem by taking into account the visible area of individual sequences as well as the network constraint. We then present two solutions to decide the quality of each volumetric video in real-time. Extensive evaluation shows that the proposed framework can increase the viewport quality by <inline-formula> <tex-math>$0.5\\sim 1.1$ </tex-math></inline-formula>dB compared to existing methods. The outcome of this study is expected to accelerate the adoption of real-time interactive XR applications, enabling users to experience and interact with dynamic virtual environments seamlessly.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"25223-25238"},"PeriodicalIF":3.4000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10870276","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10870276/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Volumetric video is the emerging format for representing real-world dynamic objects such as humans in Extended Reality (XR) applications. However, real-time streaming of volumetric video to user devices is challenging due to the extremely high data rate and low latency requirements. This paper introduces NAVA, a novel network-adaptive view-aware volumetric video streaming framework for XR scenes consisting of multiple volumetric sequences. The proposed framework dynamically adapts the quality of individual volumetric sequences based on network conditions and the user’s viewpoint to optimize streaming performance under network constraints. In our framework, multiple versions with different quality of individual volumetric video are prepared and stored on the server in advance. The rate allocation problem is formulated as a optimization problem by taking into account the visible area of individual sequences as well as the network constraint. We then present two solutions to decide the quality of each volumetric video in real-time. Extensive evaluation shows that the proposed framework can increase the viewport quality by $0.5\sim 1.1$ dB compared to existing methods. The outcome of this study is expected to accelerate the adoption of real-time interactive XR applications, enabling users to experience and interact with dynamic virtual environments seamlessly.
IEEE AccessCOMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍:
IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest.
IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on:
Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals.
Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering.
Development of new or improved fabrication or manufacturing techniques.
Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.