Novel distributed virtual reality architecture based on streaming techniques

Jie Ma; Jin-wen Tian

doi:10.1117/12.750043

14 November 2007 Novel distributed virtual reality architecture based on streaming techniques

Jie Ma, Jin-wen Tian

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67904V (2007) https://doi.org/10.1117/12.750043
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

There exist irreconcilable conflict between mass data and network transfer bandwidth in traditional distributed virtual reality (DVR) systems, which has severely limited the widespread application of DVR techniques. In order to solve these problems, a novel DVR system architecture based on streaming techniques is proposed. The topology of this system is a hybrid architecture (using peer-to-peer model to transfer control information, using hierarchy model to transfer data information), which is helpful to overcome the communication bottle-neck, and the object-oriented data structure is also designed to fit for streaming techniques. In order to take full advantage of streaming techniques, multithreading and dynamic buffer can be applied to reduce network time-delay. In this paper, the implements of these techniques are introduced in detail, the result of experiments prove that: the DVR system based on streaming techniques can notably reduce the hardware requirements, increase the client number and decrease the system time-delay, as a result make the internet based desktop DVR system available.

Citation Download Citation

Jie Ma and Jin-wen Tian "Novel distributed virtual reality architecture based on streaming techniques", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904V (14 November 2007); https://doi.org/10.1117/12.750043

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available