Method and system for recommending one or more gestures to users interacting with computing device

• US 9,965,043 B2
• Filed: 03/14/2016
• Issued: 05/08/2018
• Est. Priority Date: 01/27/2016
• Status: Active Grant

• Current Assignee: Wipro Limited
• Original Assignee: Wipro Limited
• Inventors: Mishra, Bibhunanda
• Primary Examiner(s): Bhargava, Anil
• Application Number:
  US15/069,135
• Publication Number:
  US 20170212597A1
• Time in Patent Office: 785 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 9/453 Help systems
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113

Abstract

The present disclosure relates to a method and a system for recommending one or more gestures to a user interacting with a computing device. The system receives gesture data from one or more sensors. Based on the gesture data, for each gesture, system determines a noise score and at least one of proximity score, shape score, and strength score. The noise score is set in order to rank gesture based on the mistake made by user or each time when the gesture was not detected properly by the system. Based on the noise score and at least one of the proximity score, shape score, and strength score, a cumulative score is calculated. If the cumulative score is above a predefined cumulative score then user is recommended to change the gesture. If the cumulative score is below the predefined cumulative score then user is recommended to improve gesture.

Claims

1. A method for recommending one or more gestures to a user interacting with a computing device, the method comprising:

receiving, by a gesture recommendation system, gesture data from one or more gesture detection sensors for each of the one or more gestures;

determining, by the gesture recommendation system, a noise score, a proximity score, a shape score, and a strength score based on the gesture data;

determining, by the gesture recommendation system, a cumulative score using the noise score, the proximity score, the shape score, and the strength score, wherein the proximity score is calculated based on a first score determined based on a body proximity range and a second score determined based on a phone proximity range, and wherein the first score is indicative of a first distance between body parts of the user associated with the one or more gestures from the body of the user and the second score is indicative of a second distance between the body parts from the computing device; and

recommending, by the gesture recommendation system, suggestions as to at least of improving the one or more gestures and changing the one or more gestures based on the cumulative score.

2. The method as claimed in claim 1, wherein the suggestions are recommended to improve the one or more gestures when the cumulative score is less than a predefined cumulative score.

3. The method as claimed in claim 1, wherein the suggestions are recommended to change the one or more gestures when the cumulative score is more than a predefined cumulative score.

4. The method as claimed in claim 1, wherein the one or more gesture detection sensors comprise at least of a proximity sensor, radar, image sensor, or infrared muscle contraction sensor.

5. The method as claimed in claim 1, wherein the shape score is determined based on number of body parts required and angular movement of the body parts required to make the one or more gestures.

6. The method as claimed in claim 1, wherein the strength score is determined based on number of muscles used to make the one or more gestures.

7. The method as claimed in claim 1, wherein the noise score is determined based on at least one of false positives associated with the one or more gestures and errors detected with the one or more gestures.

8. A gesture recommendation system for recommending one or more gestures to a user interacting with a computing device, the gesture recommendation system comprising:

at least one processor; and

a memory storing instructions executable by the at least one processor, wherein the instructions configure the at least one processor to;

receive gesture data from one or more gesture detection sensors for each of the one or more gestures;

determine a noise score, a proximity score, a shape score and a strength score based on the gesture data;

determine a cumulative score using the noise score, the proximity score, the shape score, and the strength score, wherein the proximity score is calculated based on a first score determined based on a body proximity range and a second score determined based on a phone proximity range, and wherein the first score is indicative of a first distance between body parts of the user associated with the one or more gestures from the body of the user and the second score is indicative of a second distance between the body parts from the computing device; and

recommend suggestions as to at least of improving the one or more gestures and changing the one or more gestures based on the cumulative score.

9. The gesture recommendation system as claimed in claim 8, wherein the processor recommends suggestions to improve the one or more gestures when the cumulative score is less than a predefined cumulative score.

10. The gesture recommendation system as claimed in claim 8, wherein the processor recommends suggestions to change the one or more gestures when the cumulative score is more than a predefined cumulative score.

11. The gesture recommendation system as claimed in claim 8, wherein the one or more gesture detection sensors comprise at least of a proximity sensor, radar, image sensor or infrared muscle contraction sensor.

12. The gesture recommendation system as claimed in claim 8, wherein the processor determines the shape score based on number of body parts required and angular movement of the body parts required to make the one or more gestures.

13. The gesture recommendation system as claimed in claim 8, wherein the processor determines the strength score based on number of muscles used to make the one or more gestures.

14. The gesture recommendation system as claimed in claim 8, wherein the processor determines the noise score based on at least one of false positives associated with the one or more gestures and errors detected with the one or more gestures.

15. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a gesture recommendation system to perform the operations comprising:

receiving gesture data from one or more gesture detection sensors for each of the one or more gestures;

determining a noise score, a proximity score, a shape score and a strength score based on the gesture data;

determining a cumulative score using the noise score and at least one of the proximity score, the shape score, and the strength score, wherein the proximity score is calculated based on a first score determined based on a body proximity range and a second score determined based on a phone proximity range, and wherein the first score is indicative of a first distance between body parts of the user associated with the one or more gestures from the body of the user and the second score is indicative of a second distance between the body parts from the computing device; and

recommending suggestions as to at least of improving the one or more gestures and changing the one or more gestures based on the cumulative score.

16. The non-transitory computer readable medium as claimed in claim 15, wherein the instructions cause the processor to determine the shape score based on number of body parts required and angular movement of the body parts required to make the one or more gestures.

17. The non-transitory computer readable medium as claimed in claim 15, wherein the instructions cause the processor to determine the strength score based on number of muscles used to make the one or more gestures and noise score based on at least one of false positives associated with the one or more gestures and errors detected with the one or more gestures.