Abstract
Second order polynomials are commonly used for estimating the point-of-gaze in headmounted eye trackers. Studies in remote (desktop) eye trackers show that although some non- standard 3rd order polynomial models could provide better accuracy, high-order polynomials do not necessarily provide better results. Different than remote setups though, where gaze is estimated over a relatively narrow field-of-view surface (e.g. less than 30×20 degrees on typical computer displays), head-mounted gaze trackers (HMGT) are often desired to cover a relatively wider field-of-view to make sure that the gaze is detected in the scene image even for extreme eye angles. In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions. Using simulated scenarios, we describe effects of four different sources of error: interpolation, extrapolation, parallax, and radial distortion. We show that the use of third order polynomials result in more accurate gaze estimates in HMGT, and that the use of wide angle lenses might be beneficial in terms of error reduction.
Highlights
Diako MardanbegiSecond order polynomials are commonly used for estimating the point-of-gaze in headmounted eye trackers
Monocular video-based head mounted gaze trackers use at least one camera to capture the eye image and another to capture the field-of-view (FoV) of the user
In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions
Summary
Second order polynomials are commonly used for estimating the point-of-gaze in headmounted eye trackers. Different than remote setups though, where gaze is estimated over a relatively narrow field-of-view surface (e.g. less than 30 × 20 degrees on typical computer displays), head-mounted gaze trackers (HMGT) are often desired to cover a relatively wider field-of-view to make sure that the gaze is detected in the scene image even for extreme eye angles. In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions. We show that the use of third order polynomials result in more accurate gaze estimates in HMGT, and that the use of wide angle lenses might be beneficial in terms of error reduction
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