{"title":"Light field video streaming on GPU","authors":"Tomáš Chlubna , Tomáš Milet , Pavel Zemčík","doi":"10.1016/j.image.2025.117377","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes an efficient encoding method for light field video rendering in real time. Each frame of the light field video consists of a grid of images capturing the scene from different camera positions. The images are encoded by a video compression algorithm. The positions of the keyframes on the grid are automatically determined. The proposed compression uses GPU-accelerated HW video decoders. Data transfer between the host and the GPU memory is minimal. Only the packets necessary for the novel view synthesis are transferred. Standard video compression methods need to decode all packets between keyframes, and other existing light field compression methods focus solely on the best compression ratio. The proposed method outperforms them in the quality/decoding time ratio, which is the most important metric for the real-time rendering. The results presented show that currently existing alternatives cannot be used efficiently for 4K light field video streaming. A proof-of-concept light field player was implemented and is available to use. The proposal solves the memory and streaming requirements that are the most crucial issues in light field rendering. The paper additionally outlines enhancements to a current light field rendering technique, which has been modified to integrate effectively with the newly proposed encoding method.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117377"},"PeriodicalIF":3.4000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing-Image Communication","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0923596525001237","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an efficient encoding method for light field video rendering in real time. Each frame of the light field video consists of a grid of images capturing the scene from different camera positions. The images are encoded by a video compression algorithm. The positions of the keyframes on the grid are automatically determined. The proposed compression uses GPU-accelerated HW video decoders. Data transfer between the host and the GPU memory is minimal. Only the packets necessary for the novel view synthesis are transferred. Standard video compression methods need to decode all packets between keyframes, and other existing light field compression methods focus solely on the best compression ratio. The proposed method outperforms them in the quality/decoding time ratio, which is the most important metric for the real-time rendering. The results presented show that currently existing alternatives cannot be used efficiently for 4K light field video streaming. A proof-of-concept light field player was implemented and is available to use. The proposal solves the memory and streaming requirements that are the most crucial issues in light field rendering. The paper additionally outlines enhancements to a current light field rendering technique, which has been modified to integrate effectively with the newly proposed encoding method.
期刊介绍:
Signal Processing: Image Communication is an international journal for the development of the theory and practice of image communication. Its primary objectives are the following:
To present a forum for the advancement of theory and practice of image communication.
To stimulate cross-fertilization between areas similar in nature which have traditionally been separated, for example, various aspects of visual communications and information systems.
To contribute to a rapid information exchange between the industrial and academic environments.
The editorial policy and the technical content of the journal are the responsibility of the Editor-in-Chief, the Area Editors and the Advisory Editors. The Journal is self-supporting from subscription income and contains a minimum amount of advertisements. Advertisements are subject to the prior approval of the Editor-in-Chief. The journal welcomes contributions from every country in the world.
Signal Processing: Image Communication publishes articles relating to aspects of the design, implementation and use of image communication systems. The journal features original research work, tutorial and review articles, and accounts of practical developments.
Subjects of interest include image/video coding, 3D video representations and compression, 3D graphics and animation compression, HDTV and 3DTV systems, video adaptation, video over IP, peer-to-peer video networking, interactive visual communication, multi-user video conferencing, wireless video broadcasting and communication, visual surveillance, 2D and 3D image/video quality measures, pre/post processing, video restoration and super-resolution, multi-camera video analysis, motion analysis, content-based image/video indexing and retrieval, face and gesture processing, video synthesis, 2D and 3D image/video acquisition and display technologies, architectures for image/video processing and communication.