Nowadays, the use of eyetracking to determine 2-D gaze positions is common practice, and several approaches to the detection of 2-D fixations exist, but ready-to-use algorithms to determine eye movements in three dimensions are still missing. Here we present a dispersion-based algorithm with an ellipsoidal bounding volume that estimates 3D fixations. Therefore, 3D gaze points are obtained using a vector-based approach and are further processed with our algorithm. To evaluate the accuracy of our method, we performed experimental studies with real and virtual stimuli. We obtained good congruence between stimulus position and both the 3D gaze points and the 3D fixation locations within the tested range of 200-600 mm. The mean deviation of the 3D fixations from the stimulus positions was 17 mm for the real as well as for the virtual stimuli, with larger variances at increasing stimulus distances. The described algorithms are implemented in two dynamic linked libraries (Gaze3D.dll and Fixation3D.dll), and we provide a graphical user interface (Gaze3DFixGUI.exe) that is designed for importing 2-D binocular eyetracking data and calculating both 3D gaze points and 3D fixations using the libraries. The Gaze3DFix toolkit, including both libraries and the graphical user interface, is available as open-source software at https://github.com/applied-cognition-research/Gaze3DFix .

No abstract

The knowledge about the usual size of objects—familiar size—is known to be a taken into account for distance perception. The influence of familiar size on action programming is less clear and has not yet been tested with regard to vergence eye movements. In two experiments, we stereoscopically presented everyday objects, such as a credit card or a package of paper tissues, and varied the distance as specified by binocular disparity and the distance as specified by familiar size. Participants had to fixate the shown object and subsequently reach towards it either with open or with closed eyes. When binocular disparity and familiar size were in conflict, reaching movements revealed a combination of the two depth cues with individually different weights. The influence of familiar size was larger when no visual feedback was available during the reaching movement. Vergence movements closely followed binocular disparity and were largely unaffected by familiar size. In sum, the results suggest that in this experimental setting familiar size is taken into account for programming and executing reaching movements while vergence movements are primarily based on binocular disparity.

No abstract