Custom Gestures

• US 20140033136A1
• Filed: 07/25/2012
• Published: 01/30/2014
• Est. Priority Date: 07/25/2012
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: St. Clair, Luke
• Granted Patent: US 9,619,037 B2
• Time in Patent Office: Days
• US Class Current: 715/863
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

In one embodiment, a method includes identifying a touch input made by a user of a computing device on a touch screen of the computing device as a particular one of a plurality of custom touch gestures of the user stored on the computing device; determining the particular one of the user inputs corresponding to the particular one of the custom touch gestures identified as the touch gesture made by the user; and executing one or more actions based on the particular one of the user inputs.

Claims

1. A method comprising:

identifying, by a computing device, a touch input made by a user of the computing device on a touch screen of the computing device as a particular one of a plurality of custom touch gestures of the user stored on the computing device, each of the custom touch gestures having been recorded and assigned to a particular one of a plurality of user inputs by the computing device in response to an instruction from the user;

determining, by the computing device, the particular one of the user inputs corresponding to the particular one of the custom touch gestures identified as the touch gesture made by the user; and

executing, by the computing device, one or more actions based on the particular one of the user inputs.

2. The method of claim 1, wherein one or more of the custom touch gestures comprise a touch trajectory determined based at least in part on a machine-learning algorithm.

3. The method of claim 1, wherein the actions comprise navigating from a user interface (UI) of a home or locked screen of the computing device to a UI of a particular application on the computing device.

4. The method of claim 1, wherein the actions comprise launching an application on the computing device from a shell of an operating system (OS) running on the computing device.

5. The method of claim 1, wherein the actions comprise adjusting a controllable parameter of an application on the computing device.

6. The method of claim 1, wherein the computing device is a smartphone.

7. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

identify a touch input made by a user of a computing device on a touch screen of the computing device as a particular one of a plurality of custom touch gestures of the user stored on the computing device, each of the custom touch gestures having been recorded and assigned to a particular one of a plurality of user inputs by the computing device in response to an instruction from the user;

determine the particular one of the user inputs corresponding to the particular one of the custom touch gestures identified as the touch gesture made by the user; and

execute one or more actions based on the particular one of the user inputs.

8. The media of claim 7, wherein one or more of the custom touch gestures comprise a touch trajectory determined based at least in part on a machine-learning algorithm.

9. The media of claim 7, wherein the actions comprise navigating from a user interface (UI) of a home or locked screen of the computing device to a UI of a particular application on the computing device.

10. The media of claim 7, wherein the actions comprise launching an application on the computing device from a shell of an operating system (OS) running on the computing device.

11. The media of claim 7, wherein the actions comprise adjusting a controllable parameter of an application on the computing device.

12. The media of claim 7, wherein the computing device is a smartphone.

13. A device comprising:

one or more processors; and

one or more computer-readable non-transitory storage media coupled to the processors and embodying software that is operable when executed by the processors to;

identify a touch input made by a user of the device on a touch screen of the device as a particular one of a plurality of custom touch gestures of the user stored on the device, each of the custom touch gestures having been recorded and assigned to a particular one of a plurality of user inputs by the device in response to an instruction from the user;

determine the particular one of the user inputs corresponding to the particular one of the custom touch gestures identified as the touch gesture made by the user; and

execute one or more actions based on the particular one of the user inputs.

14. The device of claim 13, wherein one or more of the custom touch gestures comprise a touch trajectory determined based at least in part on a machine-learning algorithm.

15. The device of claim 13, wherein the actions comprise navigating from a user interface (UI) of a home or locked screen of the computing device to a UI of a particular application on the computing device.

16. The device of claim 13, wherein the actions comprise launching an application on the computing device from a shell of an operating system (OS) running on the computing device.

17. The device of claim 13, wherein the actions comprise adjusting a controllable parameter of an application on the computing device.

18. The device of claim 13, wherein the computing device is a smartphone.