US 11,998,335 B2
Systems and methods of capturing eye-gaze data
Jatin Sharma, Sammamish, WA (US); Jonathan T. Campbell, Redmond, WA (US); Jay C. Beavers, Duvall, WA (US); and Peter John Ansell, Renton, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Apr. 19, 2021, as Appl. No. 17/234,568.
Prior Publication US 2022/0330863 A1, Oct. 20, 2022
Int. Cl. A61B 5/16 (2006.01); A61B 5/00 (2006.01)
CPC A61B 5/163 (2017.08) [A61B 5/7267 (2013.01); A61B 5/7435 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A computer-implemented method for collecting eye-gaze data as training data for an eye-gaze prediction model, the method comprising:
selecting a scan path from a set of predetermined scan paths, wherein each scan path is non-self-overlapping on a screen of a device, the scan path passes through a point in a region of a series of regions in a grid on the screen, and the point represents an expected value of uniformly distributed random eye-gaze points in the region;
displaying a symbol as an eye-gaze target on the screen, wherein the eye-gaze target moves along the scan path for guiding attention of the operator;
receiving a combination of eye-gaze point data and input images associated with a plurality of points along the scan path as training data for the eye-gaze prediction model;
training the eye-gaze prediction model using the training data, wherein the eye-gaze prediction model includes data associated with parameters in one or more neural networks; and
updating the parameters in the one or more neural networks using the trained eye-gaze prediction model.