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Point-of-gaze estimation in three dimensions

University of British Columbia

Binocular eye-gaze tracking can be used to estimate the point-of-gaze (POG) of a subject in real-world three-dimensional (3D) space using the vergence of the eyes. In this thesis, a novel non-contact, model-based technique for 3D POG estimation is presented. The non-contact system allows people to select real-world objects in 3D physical space using their eyes, without the need for head-mounted equipment. Using a model-based POG estimation algorithm allows for free head motion and a single stage of calibration. The users were free to naturally move and reorient their heads while operating the system, within an allowable headspace of 3.2 x 9.2 x 14 cm. A rela tively high precision, as measured by the standard deviation of the 3D POG estimates, was measured to be 0.26 cm and was achieved with the use of high speed sampling and digital filtering techniques. When observing points in a 3D volume, large head and eye rotations are far more common than when observing a 2D screen. A novel corneal reflection pattern matching algorithm is presented for increasing image feature tracking reliability in the presence of large eye rotations. It is shown that an average accuracy of 3.93 cm was achieved over seven different subjects and a workspace volume of 30 x 23 x 25 cm (width x height x depth). An example application is presented illustrating the use of the 3D POG as a human computer interface in a 3D game of Tic-Tac-Toe on a 3 x 3 x 3 volumetric display.

Thesis/Dissertation

application/pdf

2008-12-04

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/2837

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/