Gesture fingerprinting

• US 9,501,171 B1
• Filed: 08/07/2014
• Issued: 11/22/2016
• Est. Priority Date: 10/15/2012
• Status: Active Grant

• Current Assignee: Amaze Software Incorporated
• Original Assignee: Famous Industries Incorporated (Famous Enterprises)
• Inventors: Newcomb, Steven E, Lu, Mark H
• Primary Examiner(s): Osorio, Ricardo L
• Application Number:
  US14/454,441
• Time in Patent Office: 838 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 2203/04104 Multi-touch detection in digitiser, i.e. details about the simultaneous detection of a plurality of touching locations, e.g. multiple fingers or pen and finger
• CPC Class Codes: G06F 2203/04808 Several contacts: gestures triggering a specific function, e.g. scrolling, zooming, right-click, when the user establishes several contacts with the surface simultaneously; e.g. using several fingers or a combination of fingers and pen
• CPC Class Codes: G06F 3/0485 Scrolling or panning
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06F 9/451 Execution arrangements for user interfaces

Abstract

Various implementations related to gesture fingerprinting are described. In one such implementation, a computer-implemented method includes receiving input from a user entered via an input device; determining a gesture and one or more attributes associated with the gesture based on the input; matching the gesture to a gesture model for the user using the one or more attributes; and optimizing the gesture model based on subsequent input received from the user.

Claims

1. A computer-implemented method comprising:

receiving, using one or more computing devices, input from a user entered via an input device;

determining, using the one or more computing devices, a gesture and one or more attributes associated with the gesture based on the input;

matching, using the one or more computing devices, the gesture to a gesture model for the user using the one or more attributes, the gesture model being initially patterned after how a segment of users input the gesture to perform an action;

receiving, using the one or more computing devices, one or more subsequent inputs from the user entered via the input device to perform the action;

determining, by the one or more computing devices, based on the one or more subsequent inputs, whether the gesture model is appropriate for the user; and

responsive to determining the gesture model is not appropriate for the user, automatically adjusting, using the one or more computing devices, the gesture model by self-adapting the gesture model to improve overall experience for the user in a future iteration.

2. The computer-implemented method of claim 1, further comprising:

defining, using the one or more computing devices, a plurality of gesture models including the gesture model, the plurality of gesture models being associated with a plurality of users including the user.

3. The computer-implemented method of claim 2, wherein the plurality of gesture models represent a plurality of different variations of gestures performable by users using computing devices.

4. The computer-implemented method of claim 1, wherein the gesture model is predefined for a particular variation of gesture and stored in a data store.

5. The computer-implemented method of claim 1, wherein the input reflects an input provided by the user using a touch-based user interface.

6. The computer-implemented method of claim 1, wherein matching the gesture to the gesture model associated with the user using the one or more attributes includes analyzing the one or more attributes to determine a variation of the gesture and querying a data store for a matching gesture model based on the variation.

7. A system comprising:

one or more processors; and

one or more memories storing instructions that, when executed by the one or more processors, cause the system to perform operations including;

receiving input from a user entered via an input device;

determining a gesture and one or more attributes associated with the gesture based on the input;

matching the gesture to a gesture model for the user using the one or more attributes, the gesture model being initially patterned after how a segment of users input the gesture to perform an action;

receiving one or more subsequent inputs from the user entered via the input device to perform the action;

determining, based on the one or more subsequent inputs, whether the gesture model is appropriate for the user; and

responsive to determining the gesture model is not appropriate for the user, automatically adjusting the gesture model by self-adapting the gesture model to improve overall experience for the user in a future iteration.

8. The system of claim 7, wherein the instructions, when executed by the one or more processors, further cause the system to perform operations including:

defining a plurality of gestures models including the gesture model, the plurality of gesture models being associated with a plurality of users including the user.

9. The system of claim 8, wherein the plurality of gesture models represent a plurality of different variations of gestures performable by users using computing devices.

10. The system of claim 7, wherein the gesture model is predefined for a particular variation of gesture and stored in a data store.

11. The system of claim 7, wherein the input reflects an input provided by the user using a touch-based user interface.

12. The system of claim 7, wherein matching the gesture to the gesture model associated with the user using the one or more attributes includes analyzing the one or more attributes to determine a variation of the gesture and querying a data store for a matching gesture model based on the variation.

13. A system comprising:

one or more processors;

an interpretation module executable by the one or more processors to interpret a gesture and one or more attributes associated with the gesture based on input received from a user on a computing device via an input device;

an application module coupled to the interpretation module or a data store to receive a gesture model and executable by the one or more processors to match the gesture to a gesture model for the user using the one or more attributes, the gesture model being initially patterned after how a segment of users input the gesture to perform an action; and

a learning module executable by the one or more processors to;

receive one or more subsequent inputs from the user entered via the input device to perform the action;

determine, based on the one or more subsequent inputs, whether the gesture model is appropriate for the user; and

responsive to determining the gesture model is not appropriate for the user, automatically adjust the gesture model by self-adapting the gesture model to improve overall experience for the user in a future iteration.

14. The system of claim 13, further comprising:

the data store storing a plurality of gestures models including the gesture model, the plurality of gesture models being associated with a plurality of users including the user.

15. The system of claim 14, wherein the plurality of gesture models represent a plurality of different variations of gestures performable by users using computing devices.

16. The system of claim 13, wherein the input reflects an input provided by the user using a touch-based user interface.

17. The system of claim 13, wherein to match the gesture to the gesture model associated with the user using the one or more attributes includes analyzing the one or more attributes to determine a variation of the gesture and querying the data store for a matching gesture model based on the variation.