A Tool for Estimating Success Rates of Raycasting-Based Object Selection in Virtual Reality

TL;DR

This paper introduces a practical tool integrated with Unity that estimates success rates for raycasting-based object selection in VR, aiming to enhance UI design and usability in XR applications.

Contribution

It presents a novel system that bridges research on target-pointing performance with practical VR development tools, validated through developer feedback.

Findings

The tool effectively estimates success rates in VR object selection.

VR developers found the tool useful for UI design.

The underlying theory of success rate estimation is validated.

Abstract

As XR devices become widespread, 3D interaction has become commonplace, and UI developers are increasingly required to consider usability to deliver better user experiences. The HCI community has long studied target-pointing performance, and research on 3D environments has progressed substantially. However, for practitioners to directly leverage research findings in UI improvements, practical tools are needed. To bridge this gap between research and development in VR systems, we propose a system that estimates object selection success rates within a development tool (Unity). In this paper, we validate the underlying theory, describe the tool's functions, and report feedback from VR developers who tried the tool to assess its usefulness.