Touch gesture detection assessment

• US 10,488,975 B2
• Filed: 12/23/2015
• Issued: 11/26/2019
• Est. Priority Date: 12/23/2015
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Yeung, Fai, Ren, Jinkui, Li, Tingqian, Chen, Tong, Meunier, Gregory
• Primary Examiner(s): Cheng, Joe H
• Application Number:
  US15/774,667
• Publication Number:
  US 20180329565A1
• Time in Patent Office: 1,434 Days
• 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 3/0414 using force sensing means to determine a position
• CPC Class Codes: G06F 3/0416 Control or interface arrangements specially adapted for digitisers
• CPC Class Codes: G06F 3/04186 Touch location disambiguation
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text

Abstract

Embodiments are directed to gesture recognition in a computing device. Touch-based input by the user is monitored based on an output from a touch sensor. Gestures are directed from among the touch-based input. The detected gestures are analyzed to assign gesture characteristic profiles to the detected gestures according to profiling criteria. A sequential event log is tabulated representing counts of series of gestures based on assigned characteristic profiles and on temporal sequencing of the gestures. Circumstances for invocation of gesture detection re-calibration are assessed based on the tabulated series of gestures.

Claims

1. A system for gesture recognition in a computing device;

the system comprising;

computing hardware, including a processor, a data store, and an input device including a touch sensor, the computing hardware containing instructions, that when executed on the processor, cause the computing hardware to implement;

a gesture detection engine to monitor touch-based input by the user based on an output from the touch sensor, and to detect gestures from among the touch-based input;

a profile assignment engine to assign gesture characteristic profiles to the detected gestures according to profiling criteria;

a sequential event logging engine to tabulate and count series of gestures based on assigned characteristic profiles and on temporal sequencing of the gestures; and

an analysis engine to assess circumstances for invocation of gesture detection re-calibration based on the tabulated series of gestures.

2. The system of claim 1, wherein the touch sensor includes a multi-axial accelerometer.

3. The system of claim 1, wherein the computing hardware includes a plurality of diverse touch sensors, and wherein the gesture detection engine is to monitor and integrate output from the plurality of diverse touch sensors.

4. The system of claim 1, wherein the gesture detection engine is to apply a set of criteria to discriminate between a user gesture input, and other events sensed by the touch sensor.

5. The system of claim 1, wherein the gesture characteristic profiles include profiles representing a plurality of force-of-touch measures.

6. The system of claim 1, wherein the sequential event logging engine is to produce a data structure populated with counts of various gestures and non-gesture motion-based events.

7. The system of claim 1, wherein the analysis engine is to assess any failed detections of gestures based on the tabulated and counted series of gestures by detection of successful gesture attempts in close succession following events that fail to meet gesture detection criteria.

8. The system of claim 1, wherein the analysis engine is to assess any false detections of gestures based on the tabulated and counted series of gestures by detection of undo actions in close succession to detected gestures.

9. The system of claim 1, wherein the analysis engine is to assess any repeated gesture attempts following a non-detection of a gesture based on the tabulated and counted series of gestures.

10. The system of claim 1, wherein the analysis engine is to initiate a call for gesture detection recalibration in response to a tabulated quantity of false detection/failed detection events having occurred during a monitoring period.

11. The system of claim 1, wherein the computing device is a wearable device.

12. The system of claim 1, wherein the computing device is a mobile computing device.

13. At least one non-transitory computer-readable medium comprising instructions that, when executed on a computing device that includes a processor, a data store, and an input device including a touch sensor, cause the computing device to implement:

a gesture detection engine to monitor touch-based input by the user based on an output from the touch sensor, and to detect gestures from among the touch-based input;

a profile assignment engine to assign gesture characteristic profiles to the detected gestures according to profiling criteria;

a sequential event logging engine to tabulate and count series of gestures based on assigned characteristic profiles and on temporal sequencing of the gestures; and

an analysis engine to assess circumstances for invocation of gesture detection re-calibration based on the tabulated series of gestures.

14. The at least one computer-readable medium of claim 13, wherein the gesture characteristic profiles include profiles representing a plurality of force-of-touch measures.

15. The at least one computer-readable medium of claim 13, wherein the sequential event logging engine is to produce a data structure populated with counts of various gestures and non-gesture motion-based events.

16. The at least one computer-readable medium of claim 13, wherein the analysis engine is to assess any failed detections of gestures based on the tabulated and counted series of gestures by detection of successful gesture attempts in close succession following events that fail to meet gesture detection criteria.

17. The at least one computer-readable medium of claim 13, wherein the analysis engine is to assess any false detections of gestures based on the tabulated and counted series of gestures by detection of undo actions in close succession to detected gestures.

18. The at least one computer-readable medium of claim 13, wherein the analysis engine is to assess any repeated gesture attempts following a non-detection of a gesture based on the tabulated and counted series of gestures.

19. The at least one computer-readable medium of claim 13, wherein the analysis engine is to initiate a call for gesture detection recalibration in response to a tabulated quantity of false detection/failed detection events having occurred during a monitoring period.

20. A method for autonomously assessing gesture recognition in a computing device that includes a processor, a data store, and an input device including a touch sensor, the method comprising:

monitoring, by the computing device, touch-based input by the user based on an output from the touch sensor;

detecting, by the computing device, gestures from among the touch-based input;

assigning, by the computing device, gesture characteristic profiles to the detected gestures according to profiling criteria;

tabulating and counting, by the computing device, series of gestures based on assigned characteristic profiles and on temporal sequencing of the gestures; and

assessing, by the computing device, circumstances for invocation of gesture detection re-calibration based on the tabulated series of gestures.

21. The method of claim 20, wherein tabulating and counting the series of gestures includes producing a data structure populated with counts of various gestures and non-gesture motion-based events.

22. The method of claim 20, wherein assessing the circumstances for invocation of gesture detection re-calibration includes assessing any failed detections of gestures based on the tabulated and counted series of gestures by detecting successful gesture attempts in close succession following events that fail to meet gesture detection criteria.

23. The method of claim 20, wherein assessing the circumstances for invocation of gesture detection re-calibration includes assessing any false detections of gestures based on the tabulated and counted series of gestures by detecting undo actions in close succession to detected gestures.

24. The method of claim 20, wherein assessing the circumstances for invocation of gesture detection re-calibration includes assessing any repeated gesture attempts following a non-detection of a gesture based on the tabulated and counted series of gestures.

25. The method of claim 20, wherein assessing the circumstances for invocation of gesture detection re-calibration produces a call for gesture detection recalibration in response to a tabulated quantity of false detection/failed detection events having occurred during a monitoring period.