Towards Better Throwing: A Comparison of Performance and Preferences Across Point of Release Mechanics in Virtual Reality

Abstract

An underexplored interaction metaphor in virtual reality (VR) is throwing, with a considerable challenge in achieving accurate and natural results. We conducted an empirical investigation of partici- pants’ performance in a VR throwing task, measuring their accuracy and preferences across Point of Release (PoR) mechanics (manual and automatic) with various input device categories (hand-held, on-body, external) and throwable object types. Participants were tasked with throwing a baseball, a bowling ball, and a football to- ward targets using 5 input configurations (2 manual and 3 automatic PoR). Results from 30 participants indicate that the overall high- est accuracy was achieved with an automatic PoR configuration (on-body tracker). The post-study and VR survey results indicate that the majority of participants preferred a manual PoR configura- tion (hand-held VR controller-derived) for the throwing direction, throwing speed, and as being the closest to real-life throwing. Our findings are useful for VR researchers and developers who want to implement throwing as a technique in their applications.

Mykola Maslych

Computer Science PhD Candidate

My research interests include machine learning applied to 3D User interfaces and HCI in general.