Exploring Multiscale Navigation of Homogeneous and Dense Objects with Progressive Refinement in Virtual Reality

TL;DR

This paper introduces a progressive refinement approach for multiscale navigation in VR, improving the inspection of dense objects by analyzing user navigation styles and display modes through a user study.

Contribution

It presents a novel progressive refinement method tailored for dense, homogeneous objects in VR, and evaluates its effectiveness with a comprehensive user study.

Findings

Unstructured navigation can be faster than structured.

Selection-only display mode can be quicker than full display.

Full display mode enhances object understanding and location awareness.

Abstract

Locating small features in a large, dense object in virtual reality (VR) poses a significant interaction challenge. While existing multiscale techniques support transitions between various levels of scale, they are not focused on handling dense, homogeneous objects with hidden features. We propose a novel approach that applies the concept of progressive refinement to VR navigation, enabling focused inspections. We conducted a user study where we varied two independent variables in our design, navigation style (STRUCTURED vs. UNSTRUCTURED) and display mode (SELECTION vs. EVERYTHING), to better understand their effects on efficiency and awareness during multiscale navigation. Our results showed that unstructured navigation can be faster than structured and that displaying only the selection can be faster than displaying the entire object. However, using an everything display mode can support better location awareness and object understanding.