Boxer: A multimodal collision technique for virtual objects

Byungjoo Lee, Qiao Deng, Eve Hoggan, Antti Oulasvirta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Virtual collision techniques are interaction techniques for invoking discrete events in a virtual scene, e.g. throwing, pushing, or pulling an object with a pointer. The conventional approach involves detecting collisions as soon as the pointer makes contact with the object. Furthermore, in general, motor patterns can only be adjusted based on visual feedback. The paper presents a multimodal technique based on the principle that collisions should be aligned with the most salient sensory feedback. Boxer (1) triggers a collision at the moment where the pointer's speed reaches a minimum after first contact and (2) is synchronized with vibrotactile stimuli presented to the hand controlling the pointer. Boxer was compared with the conventional technique in two user studies (with temporal pointing and virtual batting). Boxer improved spatial precision in collisions by 26.7% while accuracy was compromised under some task conditions. No difference was found in temporal precision. Possibilities for improving virtual collision techniques are discussed.

Original languageEnglish
Title of host publicationICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
EditorsEdward Lank, Eve Hoggan, Sriram Subramanian, Alessandro Vinciarelli, Stephen A. Brewster
PublisherAssociation for Computing Machinery, Inc
Pages252-260
Number of pages9
ISBN (Electronic)9781450355438
DOIs
Publication statusPublished - 2017 Nov 3
Event19th ACM International Conference on Multimodal Interaction, ICMI 2017 - Glasgow, United Kingdom
Duration: 2017 Nov 132017 Nov 17

Publication series

NameICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
Volume2017-January

Conference

Conference19th ACM International Conference on Multimodal Interaction, ICMI 2017
Country/TerritoryUnited Kingdom
CityGlasgow
Period17/11/1317/11/17

Bibliographical note

Funding Information:
The research received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement 637991). It was supported also by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT & Future Planning (NRF-2017R1C1B2002101).

Publisher Copyright:
© 2017 ACM.

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture

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