Exploiting Position History for Efficient Remote Rendering in Networked Virtual Reality

Author:

Singhal Sandeep K.1,Cheriton David R.1

Affiliation:

1. Department of Computer Science, Stanford University, Stanford, California 94305.

Abstract

Distributed virtual reality systems require accurate, efficient remote rendering of animated entities in the virtual environment. Position, velocity, and acceleration information about each player is maintained at the player's local machine, but remote hosts must display this information in real-time to support interaction between users across the network. Prior applications have transmitted position information at the local frame rate, or they have relied on dead-reckoning protocols using higher derivative information to extrapolate entity position between less frequent updates. These approaches require considerable network bandwidth and at times exhibit poor behavior. This paper describes a position history-based protocol whose update packets contain only position information. Remote hosts extrapolate from several position updates to track the location and orientation of entities between infrequent updates. Our evaluation suggests that the position history-based protocol provides a network-scalable solution for generating smooth, accurate rendering of remote entities.

Publisher

MIT Press - Journals

Subject

Computer Vision and Pattern Recognition,Human-Computer Interaction,Control and Systems Engineering,Software

Cited by 54 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The impact of virtual technology on students’ creativity: A meta-analysis;Computers & Education;2024-07

2. Key Technologies for Networked Virtual Environments;Multimedia Tools and Applications;2023-04-03

3. Driving and Flying Simulators: A Review on Relevant Considerations and Trends;Transportation Research Record: Journal of the Transportation Research Board;2021-10-30

4. A survey on 360-degree video: Coding, quality of experience and streaming;Computer Communications;2021-09

5. A universal framework for metropolis Monte Carlo simulation of magnetic Curie temperature;Computational Materials Science;2021-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3