A Scalable Framework for Distributed Virtual Reality using Heterogeneous Processors
Document Type
Conference Proceeding
Publication Date
12-1-2006
Abstract
We propose a scalable framework for virtual reality systems in a distributed environment. As the application scope of and member participation in a virtual environment increase, information sharing among geographically distributed users becomes critical and challenging. In the proposed framework, we partition the virtual environment into a group of cells and upload them to a number of heterogeneous Internet nodes. When a user sends a request to explore the distant virtual environment, visible cells will be identified and processed in parallel to produce a minimal amount of imagery results for remote transmission. To ensure scalability, we extend our scalable occlusion culling scheme using Plenoptic Opacity Function to speed up the identification process of visible cells in a virtual environment. We perform effective occlusion culling in two passes based on a non-binary opacity definition. Our experimental results justify both the efficiency and scalability of our framework in exploring large-scale virtual environments. Keywords: distributed virtual reality, occlusion culling, logistical networking, plenoptic opacity functions.
DOI
10.1007/11941354_32
Montclair State University Digital Commons Citation
Wu, Qishi; Gao, Jinzhu; and Zhu, Michelle, "A Scalable Framework for Distributed Virtual Reality using Heterogeneous Processors" (2006). Department of Computer Science Faculty Scholarship and Creative Works. 63.
https://digitalcommons.montclair.edu/compusci-facpubs/63