Binocular disparity correction system

1 . A computer-implemented method comprising:

generating a first test pattern and a second test pattern, wherein feature locations of the first test pattern are high-probabilistically different from feature locations of the second test pattern;

displaying the first test pattern on a first display and the second test pattern on a second display;

capturing the displayed first test pattern and the displayed second test pattern simultaneously from the first display and the second display in a combined image;

determining a deviation between at least one of the captured first test pattern from the combined image and the first test pattern or the captured second test pattern from the combined image and the second test pattern; and

adjusting output to at least one of the first display or the second display based on the determined deviation.

2 . The method of claim 1 , wherein the combined image includes the captured first test pattern overlaid with the captured second test pattern and wherein the first test pattern is high-probabilistically different from the second test pattern such that the feature locations are outside of a statistical distance threshold of each other.

3 . The method of claim 2 , wherein determining the deviation further comprises distinguishing the captured first test pattern from the captured second test pattern in the combined image.

4 . The method of claim 3 , wherein distinguishing the captured first test pattern from the captured second test pattern further comprises:

identifying a first set of expected features from the first test pattern and a second set of expected features from the second test pattern;

identifying a plurality of observed features from the combined image; and

determining that a first set of observed features from the plurality of observed features corresponds to the first test pattern based on similarity with the first set of expected features and that a second set of observed features from the plurality of observed features corresponds to the second test pattern based on similarity with the second set of expected features.

5 . The method of claim 4 , wherein:

determining the deviation further comprises determining a first deviation for the first display based on comparing the first set of observed features with the first set of expected features; and

adjusting the output further comprises applying a first correction to a first output of the first display based on the first deviation.

6 . The method of claim 5 , wherein:

identifying the first set of expected features comprises building a model of points based on feature locations from the first test pattern;

identifying the plurality of observed features comprises determining locations of identified features from the combined image;

distinguishing the captured first test pattern from the captured second test pattern further comprises selecting the first set of observed features from the plurality of observed features based on a relationship matrix of points between the model of points and the first set of observed features; and

determining the first deviation is based on the relationship matrix of points.

7 . The method of claim 6 , wherein the first correction is based on the relationship matrix of points.

8 . The method of claim 1 , further comprising displaying at least one of the first test pattern or the second test pattern when a user blink is detected.

9 . The method of claim 1 , further comprising displaying at least one of the first test pattern or the second test pattern when a user gaze is detected away from at least one of the first display or the second display.

10 . The method of claim 1 , further comprising displaying at least one of the first test pattern or the second test pattern hidden in an output frame.

11 . The method of claim 1 , further comprising displaying the first test pattern asynchronously with the second test pattern.

12 . A system comprising:

at least one physical processor;

a first display;

a second display;

an image sensor device; and

physical memory comprising computer-executable instructions that, when executed by the physical processor, cause the physical processor to:

generate a first test pattern and a second test pattern, wherein feature locations of the first test pattern are high-probabilistically different from feature locations of the second test pattern;

display the first test pattern on the first display and the second test pattern on the second display;

capture, using the image sensor device, the displayed first test pattern and the displayed second test pattern simultaneously from the first display and the second display in a combined image;

determine a deviation between at least one of the captured first test pattern from the combined image and the first test pattern or the captured second test pattern from the combined image and the second test pattern; and

adjust output to at least one of the first display or the second display based on the determined deviation.

13 . The system of claim 12 , wherein the combined image includes the captured first test pattern overlaid with the captured second test pattern and wherein the first test pattern is high-probabilistically different from the second test pattern such that the feature locations are outside of a statistical distance threshold of each other.

14 . The system of claim 13 , wherein the instructions for determining the deviation further comprise instructions for distinguishing the captured first test pattern from the captured second test pattern in the combined image by:

identifying a first set of expected features from the first test pattern and a second set of expected features from the second test pattern;

identifying a plurality of observed features from the combined image; and

determining that a first set of observed features from the plurality of observed features corresponds to the first test pattern based on similarity with the first set of expected features and that a second set of observed features from the plurality of observed features corresponds to the second test pattern based on similarity with the second set of expected features.

15 . The system of claim 14 , wherein:

the instructions for determining the deviation further comprise instructions for determining a first deviation for the first display based on comparing the first set of observed features with the first set of expected features; and

the instructions for adjusting the output further comprise instructions for applying a first correction to a first output of the first display based on the first deviation.

16 . The system of claim 15 , wherein:

the instructions for identifying the first set of expected features comprise instructions for building a model of points based on feature locations from the first test pattern;

the instructions for identifying the plurality of observed features comprise instructions for determining locations of identified features from the combined image;

the instructions for distinguishing the captured first test pattern from the captured second test pattern further comprise instructions for selecting the first set of observed features from the plurality of observed features based on a relationship matrix of points between the model of points and the first set of observed features;

determining the first deviation is based on the relationship matrix of points; and

the first correction is based on the relationship matrix of points.

17 . The system of claim 12 , wherein the instructions for further displaying the first and second test patterns comprise at least one of:

instructions for displaying at least one of the first test pattern or the second test pattern when a user blink is detected;

instructions for displaying at least one of the first test pattern or the second test pattern when a user gaze is detected away from at least one of the first display or the second display;

instructions for displaying at least one of the first test pattern or the second test pattern hidden in an output frame; and

instructions for displaying the first test pattern asynchronously with the second test pattern.

18 . A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to:

generate a first test pattern and a second test pattern, wherein feature locations of the first test pattern are high-probabilistically different from feature locations of the second test pattern;

display a first test pattern on a first display and a second test pattern on a second display;

capture the displayed first test pattern and the displayed second test pattern simultaneously from the first display and the second display in a combined image;

determine a deviation between at least one of the captured first test pattern from the combined image and the first test pattern or the captured second test pattern from the combined image and the second test pattern; and

adjust output to at least one of the first display or the second display based on the determined deviation.

19 . The non-transitory computer-readable medium of claim 18 , wherein the combined image includes the captured first test pattern overlaid with the captured second test pattern and wherein the first test pattern is high-probabilistically different from the second test pattern such that the feature locations are outside of a statistical distance threshold of each other.

20 . The non-transitory computer-readable medium of claim 19 , wherein:

the instructions for determining the deviation further comprises distinguishing the captured first test pattern from the captured second test pattern in the combined image;

the instructions for determining the deviation further comprise instructions for determining a first deviation for the first display based on comparing a first set of observed features with a first set of expected features; and

the instructions for adjusting the output further comprise instructions for applying a first correction to a first output of the first display based on the first deviation.