Abstract
We present an approach to measure and model the parameters of human point-of-gaze (PoG) in 3D space. Our model
considers the following three parameters: position of the gaze in 3D space, volume encompassed by the gaze and time
for the gaze to arrive on the desired target.
Extracting the 3D gaze position from binocular gaze data is hindered by three problems. The first problem is the lack of
convergence - due to micro saccadic movements the optical lines of both eyes rarely intersect at a point in space. The
second problem is resolution - the combination of short observation distance and limited comfort disparity zone typical
for a mobile 3D display does not allow the depth of the gaze position to be reliably extracted. The third problem is
measurement noise - due to the limited display size, the noise range is close to the range of properly measured data.
We have developed a methodology which allows us to suppress most of the measurement noise. This allows us to
estimate the typical time which is needed for the point-of-gaze to travel in x, y or z direction. We identify three temporal
properties of the binocular PoG. The first is reaction time, which is the minimum time that the vision reacts to a stimulus
position change, and is measured as the time between the event and the time the PoG leaves the proximity of the old
stimulus position. The second is the travel time of the PoG between the old and new stimulus position. The third is the
time-to-arrive, which is the time combining the reaction time, travel time, and the time required for the PoG to settle in
the new position.
We present the method for filtering the PoG outliers, for deriving the PoG center from binocular eye-tracking data and
for calculating the gaze volume as a function of the distance between PoG and the observer. As an outcome from our
experiments we present binocular heat maps aggregated over all observers who participated in a viewing test. We also
show the mean values for all temporal properties separately for x, y and z direction averaged over all observers. We
show the typical size of a binocular area of interest for a portable autostereoscopic display, as well as typical time the 3D
vision can react to sudden changes in a 3D scene.
