A Scalability Benchmark for a Virtual Audience Perception Model in Virtual Reality

Abstract

In this paper, we describe the implementation and performance of a Virtual Audience perception model for Virtual Reality (VR). The model is a VR adaptation of an existing desktop model. The system allows a user in VR to easily build and experience a wide variety of atmospheres with small or large groups of virtual agents.The paper describes results of early evaluations for this model in VR. Our first scalability benchmark results demonstrated the ability to simultaneously handle one hundred virtual agents without significantly affecting there commended frame rate for VR applications.This research is conducted in the context of a classroom simulation software for teachers’ training.