Gesture recognition techniques

• US 8,760,395 B2
• Filed: 05/31/2011
• Issued: 06/24/2014
• Est. Priority Date: 05/31/2011
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kim, David, Hilliges, Otmar D., Izadi, Shahram, Olivier, Patrick L., Shotton, Jamie Daniel Joseph, Kohli, Pushmeet, Molyneaux, David G., Hodges, Stephen E., Fitzgibbon, Andrew W.
• Primary Examiner(s): Haley, Joseph
• Assistant Examiner(s): FRANK, EMILY J
• Application Number:
  US13/118,884
• Publication Number:
  US 20120306734A1
• Time in Patent Office: 1,120 Days
• Field of Search: None
• US Class Current: 345/156
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• 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: G06F 3/04815 Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/75 involving models
• 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

In one or more implementations, a static geometry model is generated, from one or more images of a physical environment captured using a camera, using one or more static objects to model corresponding one or more objects in the physical environment. Interaction of a dynamic object with at least one of the static objects is identified by analyzing at least one image and a gesture is recognized from the identified interaction of the dynamic object with the at least one of the static objects to initiate an operation of the computing device.

Claims

1. A method implemented by a computing device, the method comprising:

generating a static geometry model, from data describing a physical environment captured using a sensor, using one or more static objects to model corresponding one or more objects in the physical environment;

identifying interaction of a dynamic object with at least one of the static objects by analyzing the data, the identified interaction includes identifying contact between the dynamic object and the at least one of the static objects by analyzing the data; and

recognizing a gesture from the identified interaction of the dynamic object with the at least one of the static objects to initiate an operation of the computing device.

2. A method as described in claim 1, wherein the at least one image is captured subsequent to the one or more images that were used to generate the static geometry model.

3. A method as described in claim 1, wherein at least one of the static objects is a body part of a user.

4. A method as described in claim 3, wherein the at least one static object is a hand of the user and the dynamic object is another hand of the user.

5. A method as described in claim 1, wherein sensor is a camera and the data includes images captured by the camera.

6. A method as described in claim 1, wherein the operation is to form a communication that identifies the gesture for communicating to another computing device to initiate another operation of the other computing device.

7. An apparatus comprising:

a camera configured to capture depth data of a physical environment of the camera and included within a housing that is configured to be held by a user; and

one or more modules communicatively coupled to the camera and implemented at least partially in hardware, the one or more modules configured to;

generate a static geometry model, from the depth data of the physical environment captured using the camera, using one or more static objects to model corresponding one or more objects in the physical environment;

detect an orientation or position of the camera in the physical environment;

identify interaction of a dynamic object with at least one of the static objects by analyzing at least one image, the identified interaction includes identification of contact between the dynamic object and the at least one of the static objects by analyzing at least one said image; and

recognize a gesture from the detected orientation or position of the camera and the identified interaction of the dynamic object with the at least one of the static objects to initiate an operation.

8. An apparatus as described in claim 7, wherein the housing is configured to be wearable by the user or grasped by a hand of the user.

9. An apparatus as described in claim 7, wherein the detection is performed by analyzing one or more images captured by the camera of at least a part of the physical environment.

10. An apparatus as described in claim 7, wherein the identification of the interaction includes ascertaining a position or orientation of one or more parts of a body of a user.

11. An apparatus as described in claim 7, wherein at least one of the static objects is a body part of a user.

12. An apparatus as described in claim 7, wherein the at least one static object is a hand of the user and the dynamic object is another hand of the user.

13. A method implemented by a computing device, the method comprising:

generating a static geometry model, from data describing a physical environment captured using a sensor, using one or more static objects to model corresponding one or more objects in the physical environment in which at least one of the static objects is a body part of a user;

identifying interaction of a dynamic object with at least one of the static objects by analyzing the data; and

recognizing a gesture from the identified interaction of the dynamic object with the at least one of the static objects to initiate an operation of the computing device.

14. A method as described in claim 13, wherein, the identified interaction includes identifying contact between the dynamic object and the at least one of the static objects by analyzing the data.

15. A method as described in claim 13, wherein the at least one image is captured subsequent to the one or more images that were used to generate the static geometry model.

16. A method as described in claim 13, wherein the at least one static object is a hand of the user and the dynamic object is another hand of the user.

17. A method as described in claim 13, wherein sensor is a camera and the data includes images captured by the camera.

18. A method as described in claim 13, wherein the operation is to form a communication that identifies the gesture for communicating to another computing device to initiate another operation of the other computing device.