Systems and methods of eye tracking data analysis

• US 9,798,382 B2
• Filed: 04/16/2014
• Issued: 10/24/2017
• Est. Priority Date: 04/16/2013
• Status: Active Grant

• Current Assignee: META Platforms Technologies LLC (Meta Platforms, Inc. (f/k/a Facebook, Inc.))
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Johansen, Sune Alstrup, Skovsgaard, Henrik Hegner Tomra, Tall, Martin Henrik, Lopez, Javier San Agustin, Sztuk, Sebastian
• Primary Examiner(s): Lubit, Ryan A
• Application Number:
  US14/254,503
• Publication Number:
  US 20140306882A1
• Time in Patent Office: 1,287 Days
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Methods and systems to facilitate eye tracking data analysis are provided. Point of regard information from a first client device of a first user is received, where the point of regard information is determined by the first client device by detecting one or more eye features associated with an eye of the first user. The point of regard information is stored. A request to access the point of regard information is received, and the point of regard information is sent in response to the request, where the point of regard information is used in a subsequent operation.

Claims

1. A method comprising:

displaying a resource associated with a study, the resource comprising a material subject to eye tracking analysis;

receiving, at a computing device, an image depicting a portion of a user, the image captured while displaying the resource and including reflections caused by light reflected from the user;

detecting one or more eye features associated with an eye of the user including detecting the one or more eye features using the reflections;

determining, using the one or more eye features, point of regard information associated with the resource, the point of regard information indicating a location on a display of the computing device at which the user was looking when the image of the portion of the user was taken;

capturing study data while displaying the resource, the study data comprising data selected from the group consisting of screen capture, blink rate, and mouse data;

presenting a calibration interface after displaying the resource, the calibration interface including one or more calibration points to calculate an accuracy of user calibration for determining the point of regard information;

determining, based on the accuracy of user calibration, an accuracy value for the resource associated with the point of regard information; and

sending the point of regard information in association with the study data and the accuracy value to a server, the server configured to provide the point of regard information and the associated study data and accuracy value to a second user for data analysis.

2. The method of claim 1, wherein the image was taken by a camera located on an eye tracking device coupled to the computing device.

3. The method of claim 1, wherein the light reflected from the user was emitted from one or more light sources located on an eye tracking device coupled to the computing device.

4. The method of claim 1, wherein the resource is one of an image, a video, a website, or a game.

5. The method of claim 1, wherein the point of regard information, the study data, and the accuracy value are accessed from the server by a second user, and wherein the second user subsequently performs an analysis of the point of regard information, the study data, and the accuracy value.

6. The method of claim 1, further comprising:

determining that the accuracy value is insufficient;

in response to the determination that the accuracy value is insufficient, presenting the calibration interface after displaying a second resource to perform an updated calibration; and

updating the accuracy value based on one or more eye features detected during the presentation of the calibration interface.

7. The method of claim 1, wherein the data analysis comprises filtering point of regard information collected from one or more users based at least in part on the accuracy value associated with the point of regard information.

8. A non-transitory machine-readable storage medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising:

displaying a resource associated with a study, the resource comprising a material subject to eye tracking analysis;

receiving an image depicting a portion of a user, the image captured while displaying the resource and including reflections caused by light with which the user is illuminated and which is reflected from the user;

detecting one or more eye features associated with an eye of the user including detecting the one or more eye features using the reflections;

determining, using the one or more eye features, point of regard information associated with the resource, the point of regard information indicating a location on a display of the computing device at which the user was looking when the image of the portion of the user was taken;

capturing study data while displaying the resource, the study data comprising data selected from the group consisting of screen capture, blink rate, and mouse data;

presenting a calibration interface after displaying the resource, the calibration interface including one or more calibration points to calculate an accuracy of user calibration for determining the point of regard information;

determining, based on the accuracy of user calibration, an accuracy value for the resource associated with the point of regard information; and

sending the point of regard information in association with the study data and the accuracy value to a server, the server configured to provide the point of regard information and the associated study data and accuracy value to a second user for data analysis.

9. The non-transitory machine-readable medium of claim 8, wherein the image was taken by a camera located on an eye tracking device coupled to the one or more processors.

10. The non-transitory machine-readable medium of claim 8, wherein the light reflected from the user was emitted from one or more light sources located on an eye tracking device coupled to the computing device.

11. The non-transitory machine-readable medium of claim 8, wherein the resource is one of an image, a video, a website, or a game.

12. The non-transitory machine-readable medium of claim 8, wherein the point of regard information, the study data, and the accuracy value are accessed from the server by a second user, and wherein the second user subsequently performs an analysis of the point of regard information, the study data, and the accuracy value.

13. The non-transitory machine-readable medium of claim 8, wherein the one or more processors further perform operations comprising:

determining that the accuracy value is insufficient;

in response to the determination that the accuracy value is insufficient, presenting the calibration interface after displaying a second resource to perform an updated calibration; and

updating the accuracy value based on the one or more eye features detected during the presentation of the calibration interface.

14. A system, comprising:

a memory that stores instructions and;

one or more processors configured by the instructions to perform operations comprising;

displaying a resource associated with a study, the resource comprising a material subject to eye tracking analysis;

receiving an image depicting a portion of a user, the image captured while displaying the resource and including reflections caused by light with which the user is illuminated and which is reflected from the user;

detecting one or more eye features associated with an eye of the user including detecting the one or more eye features using the reflections;

determining, using the one or more eye features, point of regard information associated with the resource, the point of regard information indicating a location on a display of the computing device at which the user was looking when the image of the portion of the user was taken;

capturing study data while displaying the resource, the study data comprising data selected from the group consisting of screen capture, blink rate, and mouse data;

presenting a calibration interface after displaying the resource, the calibration interface including one or more calibration points to calculate an accuracy of user calibration for determining the point regard information;

determining, based on the accuracy of user calibration, an accuracy value for the resource associated with the point of regard information; and

sending the point of regard information in association with the study data and the accuracy value to a server, the server configured to provide the point of regard information and the associated study data and accuracy value to a second user for data analysis.

15. The system of claim 14, wherein the image was taken by a camera located on an eye tracking device coupled to the one or more processors.

16. The system of claim 14, wherein the light reflected from the user was emitted from one or more light sources located on an eye tracking device coupled to the computing device.

17. The system of claim 14, wherein the resource is one of an image, a video, a website, or a game.

18. The system of claim 17, wherein the user information includes each of the screen capture, the blink rate, and the accuracy.

19. The system of claim 14, wherein the point of regard information, the study data, and the accuracy value are capable of being accessed from the server by a second user, and wherein the second user subsequently performs an analysis of the point of regard information, the study data, and the accuracy value.