USER IDENTIFICATION BY GESTURE RECOGNITION

• US 20130004016A1
• Filed: 06/29/2011
• Published: 01/03/2013
• Est. Priority Date: 06/29/2011
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Karakotsios, Kenneth M., Ivanchenko, Volodymyr V.
• Granted Patent: US 8,693,726 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06V 40/172 Classification, e.g. identification
• 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: G06V 40/37 based only on signature signals such as velocity or pressure, e.g. dynamic signature recognition

Abstract

A user can be identified and/or authenticated to an electronic device by analyzing aspects of a motion or gesture made by that user. At least one imaging element of the device can capture image information including the motion or gesture, and can determine time-dependent information about that motion or gesture in two or three dimensions of space. The time-dependent information can be used to identify varying speeds, motions, and other such aspects that are indicative of a particular user. The way in which a gesture or motion is made, in addition to the motion or gesture itself, can be used to authenticate an individual user. While other persons can learn the basic gesture or motion, the way in which each person makes that gesture or motion will generally be at least slightly different, which can be used to prevent unauthorized access to sensitive information, protected functionality, or other such content.

Claims

1. A computer-implemented method of identifying a user of a computing device, comprising:

capturing image information using at least one image capture element of the computing device;

analyzing, by the computing device, the image information to identify a position of at least one feature of a person near the computing device;

tracking a position of the at least one feature over a period of time in the captured image information;

determining, by the computing device, a set of points including both position and time information for the feature during at least a portion of the period of time;

comparing the set of points to at least one gesture pattern stored for an authorized user of the computing device, the gesture pattern including both a path of movement for the gesture and at least one of relative timing, acceleration, or velocity information for a plurality of points along the path of movement; and

providing input indicating that the person is an authorized user of the computing device when the set of points matches one of the at least one gesture pattern stored for the authorized user with at least a minimum level of certainty,

wherein a user is able to be identified to the computing device based at least in part upon a combination of a specific gesture and a way in which the user performs that specific gesture.

2. The computer-implemented method of claim 1, wherein capturing image information is performed in response to detecting motion near the computing device.

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

authenticating an identity of the user;

prompting the user to perform a gesture to be associated with the user;

capturing image information corresponding to the user performing the gesture;

analyzing the image information to determine user-specific position and time information for the gesture; and

storing the user-specific position and time information to be used in subsequent identification of the user.

4. The computer-implemented method of claim 1, wherein the at least one gesture pattern stored for an authorized user includes at least one of a set of points, a continuous function, a set of trajectories, or at least one fit curve.

5. The computer-implemented method of claim 1, wherein the set of points includes position information in three dimensions.

6. The computer-implemented method of claim 1, wherein the at least one feature includes at least one of a hand, finger, eye, elbow, arm, or held object.

14. The computer-implemented method of claim 4, wherein the person is denied access to at least some content or functionality on the computing device when the tracked position information does not match the information stored for a gesture associated with the user with at least a minimum level of certainty.

7. A computer-implemented method of identifying a user, comprising:

under control of one or more computing devices including executable instructions,

obtaining image information captured using at least one image capture element of a computing device;

analyzing the image information to identify a position of at least one feature of a person near the computing device;

tracking a position of the at least one feature over a period of time in the captured image information;

comparing the information for the tracked position of the at least one feature to information stored for at least one gesture associated with a user, the information including at least two of a type of gesture, a path of movement associated with a gesture, relative timing information for the portions of the path of movement, and relative distances of features of the user when performing the gesture; and

providing information indicating that the user is identified when the tracked position information matches the information stored for a gesture associated with the user.

8. The computer-implemented method of claim 7, wherein the captured image information includes at least one of ambient light image information and reflected infrared image information.

9. The computer-implemented method of claim 8, further comprising:

subtracting a weighted amount of the ambient light image information from the reflected infrared image information in order to substantially remove background information from the reflected infrared image information.

10. The computer-implemented method of claim 7, wherein the captured image information is analyzed to determine the location of at least one feature of the person using at least one of image recognition, proximity detection, and intensity analysis.

11. The computer-implemented method of claim 7, wherein the gesture is a static gesture for a period of time, and wherein the information stored for the at least one gesture associated with a user includes a type of gesture and relative distances of one or more features of the user when performing the gesture.

12. The computer-implemented method of claim 7, wherein the gesture includes motion over a period of time, and wherein the information stored for the at least one gesture associated with a user includes at least one path of movement associated with a gesture and relative timing information for at least portions of the at least one path of movement.

13. The computer-implemented method of claim 7, wherein the position of the at least one feature is capable of being determined in two or three dimensions.

15. The computer-implemented method of claim 7, further comprising:

causing at least one source of illumination to be activated during at least a portion of the period of time in which the image information is captured.

16. The computer-implemented method of claim 7, wherein the at least one source of illumination includes at least one of a white light and an infrared source of illumination that is activated continuously or periodically during the period of time.

17. The computer-implemented method of claim 7, wherein at least one feature includes at least one of a hand, finger, eye, elbow, arm, or held object.

18. The computer-implemented method of claim 7, wherein the computing device stores captured image information in a rolling buffer enabling gesture analysis to include captured image information obtained up to a fixed period of time before the gesture analysis was activated.

19. The computer-implemented method of claim 7, further comprising:

fitting a curve or function to the information for the tracked position before comparing the information for the tracked position to the information stored for at least one gesture associated with the user.

20. The computer-implemented method of claim 7, further comprising:

deactivating a gesture input mode if no gesture is detected within a specified period of inactivity.

21. The computer-implemented method of claim 7, wherein the position of at least one feature of the person near the computing device is further capable of being identified and tracked over a period of time using a capacitive screen operable to detect position and motion within a given distance of the capacitive screen.

22. A computing device, comprising:

a device processor;

at least one image capture element; and

a memory device including instructions operable to be executed by the processor to perform a set of actions, enabling the computing device to;

obtain image information captured using at least one image capture element of the computing device;

analyze the image information to identify a position of at least one feature of a person near the computing device;

track a position of the at least one feature over a period of time in the captured image information;

compare the information for the tracked position of the at least one feature to information stored for at least one gesture associated with a user, the information including at least two of a type of gesture, a path of movement associated with a gesture, relative timing information for the portions of the path of movement, and relative distances of features of the user when performing the gesture; and

provide information indicating that the user is identified when the tracked position information matches the information stored for a gesture associated with the user.

23. The computing device of claim 22, further comprising:

at least one source of illumination operable to provide at least one of a white light and infrared radiation continuously or periodically during the period of time at which the image capture information is obtained.

24. The computing device of claim 22, further comprising:

a rolling data buffer operable to store a maximum amount of recently obtained image capture data, enabling gesture analysis to include captured image information obtained up to a fixed period of time before the gesture analysis was activated.

25. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to:

obtain image information captured using at least one image capture element of the computing device;

analyze the image information to identify a position of at least one feature of a person near the computing device;

track a position of the at least one feature over a period of time in the captured image information;

compare the information for the tracked position of the at least one feature to information stored for at least one gesture associated with a user, the information including at least two of a type of gesture, a path of movement associated with a gesture, relative timing information for the portions of the path of movement, and relative distances of features of the user when performing the gesture; and

provide information indicating that the user is identified when the tracked position information matches the information stored for a gesture associated with the user.

26. The non-transitory computer-readable storage medium of claim 25, wherein the captured image information includes at least one of ambient light image information and reflected infrared image information, and further comprising:

subtracting a weighted amount of the ambient light image information from the reflected infrared image information in order to substantially remove background information from the reflected infrared image information.

27. The non-transitory computer-readable storage medium of claim 25, wherein the instructions when executed further cause the processor to determine the position of the at least one feature in two or three dimensions.