EyeInfo Research Group

Paper published in the Proceedings of the 2004 Symposium on Eye Tracking Research & Applications (ETRA 2004)
Location: San Antonio, TX, USA
Date: Mar. 2004
Publisher: ACM
ISBN/ISSN: 1-58113-825-3
Pages: 58-58
DOI Bookmark: 10.1145/968363.968375

Dan Witzner Hansen, IT University of Copenhagen
David J. C. MacKay, University of Cambridge
John Paulin Hansen, IT University Copenhagen
Mads Nielsen, IT University Copenhagen

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.



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