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

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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.
Original languageEnglish
Title of host publicationCHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Number of pages14
PublisherAssociation for Computing Machinery
Publication date7 May 2021
Article number130
ISBN (Electronic)978-1-4503-8096-6/21/05
Publication statusPublished - 7 May 2021
EventCHI 2021 Virtual Conference on Human Factors in Computing Systems -
Duration: 8 May 202113 May 2021


ConferenceCHI 2021 Virtual Conference on Human Factors in Computing Systems

ID: 287611757