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Comparing visualizations for tracking off-screen moving targets

Published:28 April 2007Publication History

ABSTRACT

In games, aircraft navigation systems and in control systems, users have to track moving targets around a large workspace that may extend beyond the users. viewport. This paper presents on-going work that investigates the effectiveness of two different off-screen visualization techniques for accurately tracking off-screen moving targets. We compare the most common off-screen representation, Halo, with a new fisheye-based visualization technique called EdgeRadar. Our initial results show that users can track off-screen moving objects more accurately with EdgeRadar over Halos. This work presents a preliminary but promising step toward the design of visualization techniques for tracking off-screen moving targets.

References

  1. Baudisch, P. and Rosenholtz, R. 2003. Halo: a technique for visualizing off-screen objects. CHI '03, 481--488. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Leung, Y. K. and Apperley, M. D. 1994. A review and taxonomy of distortion-oriented presentation techniques. ACM TOCHI, v1(2), 126--160. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Pylyshyn, Z.W. and Storm, R.W. 1998. Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, v3(3), 179--197.Google ScholarGoogle Scholar
  4. Yantis, S. 1992. Multielement Visual Tracking: Attention and Perceptual Organization. Cognitive Psychology, v24(3), 295--340.Google ScholarGoogle Scholar
  5. Zellweger, P. T., Mackinlay, J. D., Good, L., Stefik, M., and Baudisch, P. 2003. City lights: contextual views in minimal space. CHI '03 Ext. Abstracts, 838--839. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Comparing visualizations for tracking off-screen moving targets

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    • Published in

      cover image ACM Conferences
      CHI EA '07: CHI '07 Extended Abstracts on Human Factors in Computing Systems
      April 2007
      1286 pages
      ISBN:9781595936424
      DOI:10.1145/1240866

      Copyright © 2007 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 April 2007

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      Acceptance Rates

      CHI EA '07 Paper Acceptance Rate212of582submissions,36%Overall Acceptance Rate6,164of23,696submissions,26%

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