Automated performance measurement framework for single platform XR particle effects in Unity3D

Abstract

This thesis investigates the optimization of particle effects in single platform VR and AR, collectively known as XR environments, using Unity3D. Previous work has highlighted the importance of maintaining high performance in XR applications especially to prevent user discomfort. Motivated by the need to find effective ways to optimize particle effects without compromising performance, this research aims to provide actionable insights for developers to enhance user experiences in VR and AR applications.

The constructive method was employed to design and implement a controlled virtual environment and develop an automated testing framework. This framework was used to simulate user interactions systematically and measure performance metrics. Data gathered from these tests were analyzed using polynomial regression to define optimized levels of particle effects for various XR modes.

The results reveal differences between the performance of particle effects in different modes, offering insights into the appropriate use of particle systems in XR environments. The automated testing framework not only proved effective for data gathering and optimization purposes but also provided a cost-effective alternative to the initially intended use of an expensive robot for testing. These findings contribute to a deeper understanding of particle system performance in XR environments and offer a robust methodology for optimizing visual effects, thereby enhancing the overall user experience in VR and AR applications.