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VisionWand: interaction techniques for large displays using a passive wand tracked in 3D

Published:01 August 2004Publication History

ABSTRACT

A passive wand tracked in 3D using computer vision techniques is explored as a new input mechanism for interacting with large displays. We demonstrate a variety of interaction techniques and visual widgets that exploit the affordances of the wand, resulting in an effective interface for large scale display interaction. The lack of any buttons or other electronics on the wand presents a challenge that we address by developing a set of gestures and postures to track and enable command input.

References

  1. Cao, X., Balakrishnan, R.(2003). VisionWand: Interaction Techniques for Large Displays using a Passive Wand Tracked in 3D. In Proceedings of UIST 2003, ACM Symposium on User Interface Software and Technology, ACM CHI Letters 5(2), p. 193--202. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. VisionWand: interaction techniques for large displays using a passive wand tracked in 3D

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    • Published in

      cover image ACM Conferences
      SIGGRAPH '04: ACM SIGGRAPH 2004 Papers
      August 2004
      684 pages
      ISBN:9781450378239
      DOI:10.1145/1186562
      • Editor:
      • Joe Marks

      Copyright © 2004 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 1 August 2004

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      Acceptance Rates

      SIGGRAPH '04 Paper Acceptance Rate83of478submissions,17%Overall Acceptance Rate1,822of8,601submissions,21%

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