A Gesture Recognition Model for Virtual Reality Motion Controllers

PubDate: Oct 2020

Teams: University of Lincoln

Writers: Christopher Headleand, Benjamin Williams, Jussi Holopainen, Marlon Gilliam

PDF: A Gesture Recognition Model for Virtual Reality Motion Controllers

Abstract

In this paper we discuss gesture recognition in the domain of Virtual Reality (VR) video games. We begin by presenting a detailed review of the literature. Furthermore, we discuss some of the specific opportunities and challenges that are specific to the VR domain. Most commercial VR devices come with tracked motion controllers as a default interface which facilitates the possibility of gesture control. However, video games specifically require a high degree of accuracy to prevent non-gesture actions being evaluated. To tackle this challenge we present a novel modification to the Hidden Markov Model gesture recognition approach. We expand on previous work with gestures in with the implementation of an adaptive database system allowing users to quickly engage with an application without significant training. Our results on a benchmark problem shows that the approach can produce impressive accuracy rates. The results from our benchmarking shows promise for the usability of gesture based interaction systems for VR devices in the future. Our system achieves high levels of recognition accuracy competitive with the best performing existing system whilst requiring minimal user independent training.