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Ninja Hands: Using Many Hands to Improve Target Selection in VR

Jonas Schjerlund,Kasper Hornbæk,Joanna Bergström

Published 2021 in International Conference on Human Factors in Computing Systems

ABSTRACT

Selection and manipulation in virtual reality often happen using an avatar’s hands. However, objects outside the immediate reach require effort to select. We develop a target selection technique called Ninja Hands. It maps the movement of a single real hand to many virtual hands, decreasing the distance to targets. We evaluate Ninja Hands in two studies. The first study shows that compared to a single hand, 4 and 8 hands are significantly faster for selecting targets. The second study complements this finding by using a larger target layout with many distractors. We find no decrease in selection time across 8, 27, and 64 hands, but an increase in the time spent deciding which hand to use. Thereby, net movement time still decreases significantly. In both studies, the physical motion exerted also decreases significantly with more hands. We discuss how these findings can inform future implementations of the Ninja Hands technique.

PUBLICATION RECORD

  • Publication year

    2021

  • Venue

    International Conference on Human Factors in Computing Systems

  • Publication date

    2021-05-06

  • Fields of study

    Computer Science

  • Identifiers
    DOI 10.1145/3411764.3445759
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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