Experimental Analysis of Freehand Multi-Object Selection Techniques in Virtual Reality Head-Mounted Displays

TL;DR

This work presents an empirical comparison of six freehand techniques, which are comprised of three mode-switching gestures and two group selection techniques derived from prior work, and demonstrates the performance, user experience, and preference of each technique.

Abstract

Object selection is essential in virtual reality (VR) head-mounted displays (HMDs). Prior work mainly focuses on enhancing and evaluating techniques for selecting a single object in VR, leaving a gap in the techniques for multi-object selection, a more complex but common selection scenario. To enable multi-object selection, the interaction technique should support group selection in addition to the default pointing selection mode for acquiring a single target. This composite interaction could be particularly challenging when using freehand gestural input. In this work, we present an empirical comparison of six freehand techniques, which are comprised of three mode-switching gestures (Finger Segment, Multi-Finger, and Wrist Orientation) and two group selection techniques (Cone-casting Selection and Crossing Selection) derived from prior work. Our results demonstrate the performance, user experience, and preference of each technique. The findings derive three design implications that can guide the design of freehand techniques for multi-object selection in VR HMDs.

Figures (5)

• Figure 1: The freehand techniques in each part of the multi-object selection process: a ray-casting technique is used for the default selection, Cone-casting Selection or Crossing Selection can do group selection, and the two modes can be transited using Finger Segment, Multi-Finger, or Wrist Orientation gestures.
• Figure 2: Illustrations for (A) experimental setup, (B) experimental task, (C) the Low Complexity condition, (D) the High Complexity condition.
• Figure 3: Plots of average ($\pm1SE$) performance under two task complexities. (A) Completion time. (B) Number of errors. (C) Number of actions. (D) Hand movements.
• Figure 4: (A) Average ($\pm1SE$) NASA scores of the techniques. The lower the score is, the lower the perceived workload of the technique (i.e., the better). (B) Average ($\pm1SE$) SUS scores of the techniques. The higher the score is, the higher the usability of the technique (i.e., the better). (C) Average ($\pm1SE$) Borg CR10 scores of the techniques. The lower the score is, the lower the perceived arm fatigue (i.e., the better). (D) Participants' ranking of each technique.
• Figure 5: The initial design of the multiple-object selection process and freehand techniques.