Custom gestures

Patent metadata

Field	Value
Publication number	US-9619037-B2
Application number	US-201213557945-A
Country	US
Kind code	B2
Filing date	Jul 25, 2012
Priority date	Jul 25, 2012
Publication date	Apr 11, 2017
Grant date	Apr 11, 2017

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.

First claim

What is claimed is:

1. A method comprising:
determining, by a computing device associated with a user of a social-networking system, that a custom-touch-gesture feature should be turned on and enabling the custom-touch-gesture feature for the computing device, wherein the determining is based on usage of the custom-touch-gesture feature by at least a threshold number of the user's social contacts within a specified social degree of separation in the social-networking system;
identifying, by the computing device, a touch gesture 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. The method of claim 1 , wherein the plurality of custom touch gestures of the user are stored in a user preference file on a remote server.

8. The method of claim 1 , wherein assigning a custom touch gesture comprises:
accessing a recording user interface of a recording application;
receiving one or more training inputs from the user within the recording user interface, the one or more training inputs comprising one or more touch trajectories;
determining a custom touch gesture based on the one or more training inputs;
presenting to the user one or more user inputs from the plurality of user inputs;
receiving an instruction from the user selecting a particular user input; and
assigning the determined custom touch gesture to the particular user input.

9. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
determine that a custom-touch-gesture feature should be turned on and enabling the custom-touch-gesture feature for a computing device, wherein the determining is based on usage of the custom-touch-gesture feature by at least a threshold number of the user's social contacts within a specified social degree of separation in a social-networking system;
identify a touch gesture 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.

10. The media of claim 9 , wherein one or more of the custom touch gestures comprise a touch trajectory determined based at least in part on a machine-learning algorithm.

11. The media of claim 9 , 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.

12. The media of claim 9 , wherein the actions comprise launching an application on the computing device from a shell of an operating system (OS) running on the computing device.

13. The media of claim 9 , wherein the actions comprise adjusting a controllable parameter of an application on the computing device.

14. The media of claim 9 , wherein the computing device is a smartphone.

15. 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:
determine that a custom-touch-gesture feature should be turned on and enabling the custom-touch-gesture feature for a computing device, wherein the determining is based on usage of the custom-touch-gesture feature by at least a threshold number of the user's social contacts within a specified social degree of separation in a social-networking system, that the custom-touch-gesture feature should be turned on and enabling the custom-touch-gesture feature for the device;
identify a touch gesture 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.

16. The device of claim 15 , wherein one or more of the custom touch gestures comprise a touch trajectory determined based at least in part on a machine-learning algorithm.

17. The device of claim 15 , 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.

18. The device of claim 15 , wherein the actions comprise launching an application on the computing device from a shell of an operating system (OS) running on the computing device.

19. The device of claim 15 , wherein the actions comprise adjusting a controllable parameter of an application on the computing device.

Assignees

• St Clair Luke
• Facebook Inc

Inventors

• St Clair Luke

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06F3/04847

  Interaction techniques to control parameter settings, e.g. interaction with sliders or dials · CPC title

• G06F3/0488

  using a touch-screen or digitiser, e.g. input of commands through traced gestures · CPC title

• G06F3/017 Primary

  Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883) · CPC title

• G06F3/04883 Primary

  for inputting data by handwriting, e.g. gesture or text · CPC title