{"title":"Web-based Mixed Reality Video Fusion with Remote Rendering","authors":"Qiang Zhou, Zhong Zhou","doi":"10.1016/j.vrih.2022.03.005","DOIUrl":null,"url":null,"abstract":"<div><p>Mixed Reality (MR) video fusion system fuses video imagery with 3D scenes. It makes the scene much more realistic and helps the users understand the video contents and temporalspatial correlation between them, thus reducing the user’s cognitive load. Nowadays, MR video fusion has been used in various applications. However, video fusion systems require powerful client machines because video streaming delivery, stitching, and rendering are computation-intensive. Moreover, huge bandwidth usage is also another critical factor that affects the scalability of video fusion systems. The framework proposed in this paper overcomes this client limitation by utilizing remote rendering. Furthermore, the framework we built is based on browsers. Therefore, the user could try the MR video fusion system with a laptop or even pad, no extra plug-ins or application programs need to be installed. Several experiments on diverse metrics demonstrate the effectiveness of the proposed framework.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 2","pages":"Pages 188-199"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virtual Reality Intelligent Hardware","FirstCategoryId":"1093","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096579622000274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Mixed Reality (MR) video fusion system fuses video imagery with 3D scenes. It makes the scene much more realistic and helps the users understand the video contents and temporalspatial correlation between them, thus reducing the user’s cognitive load. Nowadays, MR video fusion has been used in various applications. However, video fusion systems require powerful client machines because video streaming delivery, stitching, and rendering are computation-intensive. Moreover, huge bandwidth usage is also another critical factor that affects the scalability of video fusion systems. The framework proposed in this paper overcomes this client limitation by utilizing remote rendering. Furthermore, the framework we built is based on browsers. Therefore, the user could try the MR video fusion system with a laptop or even pad, no extra plug-ins or application programs need to be installed. Several experiments on diverse metrics demonstrate the effectiveness of the proposed framework.