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Eye tracking off the shelf

Published:22 March 2004Publication History

ABSTRACT

What if eye trackers could be downloaded and used immediately with standard cameras connected to a computer, without the need for an expert to setup the system? This has already the case for head trackers, so why not for eye trackers?Using components off-the-shelf (COTS) for camera-based eye tracking tasks has many advantages, but it certainly introduces several new problems as less assumptions on the system can be made. As a consequence of using COTS the price for eye tracking devices can be reduced while increasing the accessibility of these systems. Eye tracking based on COTS holds potential for a large number of possible applications such as in the games industry and eye typing [Majaranta and Räihä 2002]. Different cameras may be purchased depending on the need and the amount of money the user is willing to spend on the camera. In this framework it is not possible to use IR light sources and other novel engineered devices as they cannot be bought in a common hardware store. Very little control over the cameras and the geometry of the setup can be expected. The methods employed for eye tracking should therefore be able to handle changes in light conditions and image defocusing and scale changes [Hansen and Pece 2003]. On the same token pan-and-tilt cameras cannot be used, thus forcing such systems to be passive. Figure 1 shows a possible setup of a COTS-based eye tracker. When designing systems for the general public, it is unrealistic to assume that people are able to do camera calibration and make accurate setups of camera, monitor and user. Since little is known about the setup, would this then require a vast amount of calibration points needed for gaze estimation? That is, how many calibration points are really needed? Obviously the more calibration points are used the better the chances are to be able to infer the mapping from the image to gaze direction. It would even be possible to sample the entire function space provided sufficiently many calibration points are given. From the point of view of the users, a low number of calibration points is preferred as calibration may be considered as a tedious procedure. Systems that require many calibration points for every session are therefore not likely to succeed. It is also important to know the accuracy in gaze determination when using COTS to determine their applicability for various tasks.

References

  1. HANSEN, D. W. 2003. Comitting eye tracking. Ph.D. thesis, IT University of Copenhagen.Google ScholarGoogle Scholar
  2. HANSEN, D. W. AND PECE, A. E. 2003. Feature free iris tracking. Submitted to ICCV Workshop on AMFG.Google ScholarGoogle Scholar
  3. MACKAY, D. J. C. 1998. Introduction to Gaussian processes. In Neural Networks and Machine Learning, C. M. Bishop, Ed. NATO ASI Series. Kluwer Academic Press, 133-166.Google ScholarGoogle Scholar
  4. MAJARANTA, P. AND RÄIHÄ, K.-J. 2002. Twenty years of eye typing: Systems and design issues. In Symposium on ETRA 2002: Eye Tracking Research Applications Symposium, New Orleans, Louisiana. 944-950. Google ScholarGoogle ScholarDigital LibraryDigital Library

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            • Published in

              cover image ACM Conferences
              ETRA '04: Proceedings of the 2004 symposium on Eye tracking research & applications
              March 2004
              154 pages
              ISBN:1581138253
              DOI:10.1145/968363

              Copyright © 2004 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 22 March 2004

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              Acceptance Rates

              ETRA '04 Paper Acceptance Rate18of40submissions,45%Overall Acceptance Rate69of137submissions,50%

              Upcoming Conference

              ETRA '24
              The 2024 Symposium on Eye Tracking Research and Applications
              June 4 - 7, 2024
              Glasgow , United Kingdom

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