SYSTEMS AND METHODS FOR RECOGNITION AND TRANSLATION OF GESTURES

• US 20160042228A1
• Filed: 04/14/2015
• Published: 02/11/2016
• Est. Priority Date: 04/14/2014
• Status: Abandoned Application

• Current Assignee: MotionSavvy, Inc.
• Original Assignee: MotionSavvy, Inc.
• Inventors: Opalka, Alex, Kellard, Wade
• Application Number:
  US14/686,708
• Publication Number:
  US 20160042228A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 1/1684 Constructional details or arrangements related to integrated I/O peripherals not covered by groups G06F1/1635 - G06F1/1675
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 3/01 Input arrangements or combined input and output arrangements for interaction between user and computer G06F3/16 takes precedence
• 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 3/0304 Detection arrangements using opto-electronic means constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042
• CPC Class Codes: G06V 40/113 Recognition of static hand signs
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113
• CPC Class Codes: G09B 21/009 Teaching or communicating with deaf persons G09B21/04 takes precedence; deaf and dumb persons G09B21/00

Abstract

A system for recognizing hand gestures, comprising a gesture database configured to store information related to a plurality of gestures; a recognition controller configured to capture data related to a hand gesture being performed by a user; a recognition module configured to: determine hand characteristic information from the captured data, determine finger characteristic information from the captured data, compare the hand and finger characteristic information to the information stored in the database to determine a most likely gesture, and outputting the determined most likely gesture.

Claims

1. A system for recognizing a hand gesture, comprising:

a gesture database configured to store information related to a plurality of gestures;

a recognition controller configured to capture data related to a hand gesture being performed by a user;

a recognition module configured to;

determine hand characteristic information from the captured data,

determine finger characteristic information from the captured data,

compare the hand and finger characteristic information to the information stored in the database to determine a most likely gesture, and

outputting the determined most likely gesture.

2. The system of claim 1, wherein the gesture corresponds to a sign language number.

3. The system of claim 1, wherein the gesture corresponds to a sign language letter.

4. The system of claim 1, wherein the gesture corresponds to a sign language sign.

5. The system of claim 1, wherein the recognition module is configured to determine hand characteristic information by checking the number of hands present in the captured data, checking a palm visible time for each hand present in the captured data, checking the palm position for each visible palm, and checking a palm velocity for each visible palm.

6. The system of claim 1, wherein the recognition module is configured to determine finger characteristics by checking a number of fingers present in the capture data, checking what fingers are present, checking a finger position for fingers that are present, an checking a finger velocity of the fingers that are present.

7. The system of claim 1, wherein the recognition module is further configured to determine classifiers based on the hand and finger characteristic information.

8. The systems of claim 1, wherein the recognition module is further configured to extract features from the hand and finger characteristic information.

9. The system of claim 1, wherein the extracted features include at least one of emotion, movement, orientation, grammar, location and context.

10. A method for recognizing a hand gesture, comprising:

storing information related to a plurality of gestures in a gesture database;

using a recognition controller, capturing data related to a hand gesture being performed by a user;

determining hand characteristic information from the captured data,

determining finger characteristic information from the captured data,

comparing the hand and finger characteristic information to the information stored in the database to determine a most likely gesture, and

outputting the determined most likely gesture.

11. The method of claim 10, wherein the gesture corresponds to a sign language number.

12. The method of claim 10, wherein the gesture corresponds to a sign language letter.

13. The method of claim 10, wherein the gesture corresponds to a sign language sign.

14. The method of claim 10, further comprising determining hand characteristic information by checking the number of hands present in the captured data, checking a palm visible time for each hand present in the captured data, checking the palm position for each visible palm, and checking a palm velocity for each visible palm.

15. The method of claim 10, further comprising determining finger characteristics by checking a number of fingers present in the capture data, checking what fingers are present, checking a finger position for fingers that are present, an checking a finger velocity of the fingers that are present.

16. The method of claim 10, wherein the recognition module is further configured to determine classifiers based on the hand and finger characteristic information.

17. The method of claim 10, wherein the recognition module is further configured to extract features from the hand and finger characteristic information.

18. The method of claim 10, wherein the extracted features include at least one of emotion, movement, orientation, grammar, location and context.

19. A communication device, comprising:

a gesture database configured to store information related to a plurality of gestures;

a recognition controller configured to capture data related to a hand gesture being performed by a user;

a recognition module configured to;

determine hand characteristic information from the captured data,

determine finger characteristic information from the captured data,

compare the hand and finger characteristic information to the information stored in the database to determine a most likely gesture, and

outputting the determined most likely gesture.

20. The device of claim 19, wherein the gesture corresponds to a sign language number.

21. The device of claim 19, wherein the gesture corresponds to a sign language letter.

22. The device of claim 19, wherein the gesture corresponds to a sign language sign.

23. The device of claim 19, wherein the recognition module is configured to determine hand characteristic information by checking the number of hands present in the captured data, checking a palm visible time for each hand present in the captured data, checking the palm position for each visible palm, and checking a palm velocity for each visible palm.

24. The device of claim 19, wherein the recognition module is configured to determine finger characteristics by checking a number of fingers present in the capture data, checking what fingers are present, checking a finger position for fingers that are present, an checking a finger velocity of the fingers that are present.

25. The system of claim 19, wherein the recognition module is further configured to determine classifiers based on the hand and finger characteristic information.

26. The systems of claim 19, wherein the recognition module is further configured to extract features from the hand and finger characteristic information.

27. The system of claim 19, wherein the extracted features include at least one of emotion, movement, orientation, grammar, location and context.