Eye tracking system and methods of using an eye tracking system

1 . A method for determining a gaze convergence distance for a user of an eye tracking system, the method comprising:

receiving:

a left gaze signal, which represents a left gaze vector from a left eye origin;

a right gaze signal, which represents a right gaze vector from a right eye origin;

a combined gaze signal, which represents a determined combined gaze vector;

identifying a plurality of candidate convergence points along the combined gaze vector;

for each candidate convergence point, calculating a probability that the candidate convergence point is at the gaze convergence distance based on:

a) the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point;

b) the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point;

c) the distance between the left gaze vector and the candidate convergence point; and

d) the distance between the right gaze vector and the candidate convergence point; and

calculating the gaze convergence distance based on the candidate convergence point that has the highest probability.

2 . The method of claim 1 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

a) the application of a probability distribution function to the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point; and

b) the application of a probability distribution function to the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point.

3 . The method of claim 2 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

a) the application of one of the following probability distribution functions to the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point: a monotonically decreasing function, a normal distribution function, and a von Mises function; and

b) the application of one of the following probability distribution functions to the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point: a monotonically decreasing function, a normal distribution function, and a von Mises function.

4 . The method of claim 2 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

a) the application of a three-dimensional probability distribution function to the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point; and

b) the application of a three-dimensional probability distribution function to the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point.

5 . The method of claim 1 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

c) the application of a probability distribution function to the distance between the left gaze vector and the candidate convergence point; and

d) the application of a probability distribution function to the distance between the right gaze vector and the candidate convergence point.

6 . The method of claim 5 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

c) the application of a monotonically decreasing probability distribution function to the distance between the left gaze vector and the candidate convergence point; and

d) the application of a monotonically decreasing probability distribution function to the distance between the right gaze vector and the candidate convergence point.

7 . The method of claim 6 , wherein:

the monotonically decreasing function that is applied for the left gaze vector is an exponential function raised to the power of d, where d is distance between the left gaze vector and the candidate convergence point; and

the monotonically decreasing function that is applied for the right gaze vector is an exponential function raised to the power of d, where d is distance between the right gaze vector and the candidate convergence point.

8 . The method of claim 7 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

c) a Euclidian or a Minkowski distance between the left gaze vector and the candidate convergence point; and

d) a Euclidian or a Minkowski distance between the right gaze vector and the candidate convergence point.

9 . The method of claim 1 , further comprising:

using the determined gaze convergence distance to control the focal length of a varifocal lens of the eye tracking system.

10 . The method of claim 1 , further comprising:

presenting a plurality of selectable objects to the user on one or more display screens, wherein each of the plurality of selectable objects is at a known object distance from the user and is at a known location on the one or more display screens;

determining a gaze angle for the user at the same time as images of the user's left and right eyes are captured; and

using the calculated gaze convergence distance in combination with the determined gaze angle to identify one of the selectable objects as a selected object.

11 . The method of claim 1 , further comprising, prior to receiving the combined gaze signal, the left gaze signal, and the right gaze signal:

presenting a plurality of calibration objects to the user on one or more display screens, wherein the plurality of calibration objects is at known locations on the one or more display screens;

while the plurality of calibration objects is being presented:

capturing calibration images of the user's left eye and determining calibration left gaze signals that each represent a left gaze vector and a left eye origin for the user's left eye based on the captured calibration images of the user's left eye;

capturing calibration images of the user's right eye and determining calibration right gaze signals that each represent a right gaze vector and a right eye origin for the user's right eye based on the captured calibration images of the user's right eye;

determining:

one or more parameters of a probability distribution function for the user's left eye based on pairs of: i) a determined calibration left gaze signal; and ii) the known location of the calibration object that is displayed on the one or more display screens at the same time that the calibration image associated with the determined calibration left gaze signal was captured; and

one or more parameters of a probability distribution function for the user's right eye based on pairs of: i) a determined calibration right gaze signal; and ii) the known location of the calibration object that is displayed on the one or more display screens at the same time that the calibration image associated with the determined calibration right gaze signal was captured.

12 . An eye tracking system comprising:

an image sensor for capturing images of the eyes of the user;

one or more illuminators for illuminating the eyes of a user;

one or more controllers;

wherein the eye tracking system is configured to:

receive:

a left gaze signal, which represents a left gaze vector from a left eye origin;

a right gaze signal, which represents a right gaze vector from a right eye origin;

a combined gaze signal, which represents a determined combined gaze vector;

identify a plurality of candidate convergence points along the combined gaze vector;

for each candidate convergence point, calculate a probability that the candidate convergence point is at the gaze convergence distance based on:

a) the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point;

b) the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point;

c) the distance between the left gaze vector and the candidate convergence point; and

d) the distance between the right gaze vector and the candidate convergence point; and

calculate the gaze convergence distance based on the candidate convergence point that has the highest probability.

13 . The eye tracking system of claim 12 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

a) the application of a probability distribution function to the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point; and

b) the application of a probability distribution function to the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point.

14 . The eye tracking system of claim 12 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

a) the application of one of the following probability distribution functions to the angle between the left gaze vector and a line from the left eye origin through the candidate convergence point: a monotonically decreasing function, a normal distribution function, and a von Mises function; and

b) the application of one of the following probability distribution functions to the angle between the right gaze vector and a line from the right eye origin through the candidate convergence point: a monotonically decreasing function, a normal distribution function, and a von Mises function.

15 . The eye tracking system of claim 12 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

c) the application of a probability distribution function to the distance between the left gaze vector and the candidate convergence point; and

d) the application of a probability distribution function to the distance between the right gaze vector and the candidate convergence point.

16 . The eye tracking system of claim 15 , wherein calculating the probability that each candidate convergence point is at the gaze convergence is based on:

c) the application of a monotonically decreasing probability distribution function to the distance between the left gaze vector and the candidate convergence point; and

d) the application of a monotonically decreasing probability distribution function to the distance between the right gaze vector and the candidate convergence point.

17 . The eye tracking system of claim 12 , the eye tracking system further configured to:

use the determined gaze convergence distance to control the focal length of a varifocal lens of the eye tracking system.

18 . The eye tracking system of claim 12 , the eye tracking system further configured to:

present a plurality of selectable objects to the user on one or more display screens, wherein each of the plurality of selectable objects is at a known object distance from the user and is at a known location on the one or more display screens;

determine a gaze angle for the user at the same time as images of the user's left and right eyes are captured; and

use the calculated gaze convergence distance in combination with the determined gaze angle to identify one of the selectable objects as a selected object.

19 . The eye tracking system of claim 12 , wherein the eye tracking system is a head-mounted eye tracking system.

20 . The eye tracking system of claim 12 , wherein the eye tracking system is an extended reality system.