CONTROLLING PRIVACY IN A FACE RECOGNITION APPLICATION

• US 20170169237A1
• Filed: 12/15/2015
• Published: 06/15/2017
• Est. Priority Date: 12/15/2015
• Status: Active Grant

• Current Assignee: Hyundai Motor Company (Hyundai Motor Group), Kia Corp.
• Original Assignee: International Business Machines Corporation
• Inventors: CALO, SERAPHIN B., KO, BONG JUN, LEE, KANG-WON, SALONIDIS, THEODOROS, VERMA, DINESH C.
• Granted Patent: US 9,934,397 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 16/5854 using shape and object relationship
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06F 21/6218 to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6254 by anonymising data, e.g. decorrelating personal data from the owner's identification
• CPC Class Codes: G06F 21/83 input devices, e.g. keyboards, mice or controllers thereof
• CPC Class Codes: G06F 2221/2117 User registration
• CPC Class Codes: G06V 40/16 Human faces, e.g. facial parts, sketches or expressions
• CPC Class Codes: G06V 40/172 Classification, e.g. identification
• CPC Class Codes: H04L 63/10 for controlling access to devices or network resources
• CPC Class Codes: H04L 63/105 Multiple levels of security
• CPC Class Codes: H04W 12/08 Access security

Abstract

Embodiments of the present invention may involve a method, system, and computer program product for controlling privacy in a face recognition application. A computer may receive an input including a face recognition query and a digital image of a face. The computer may identify a target user associated with a facial signature in a first database based at least in part on a statistical correlation between a detected facial signature and one or more facial signatures in the first database. The computer may extract a profile of the target user from a second database. The profile of the target user may include one or more privacy preferences. The computer may generate a customized profile of the target user. The customized profile may omit one or more elements of the profile of the target user based on the one or more privacy preferences and/or a current context.

Claims

1. A method for controlling privacy in an application having face recognition features, the method comprising:

receiving an input including a face recognition query and a digital image of a face;

identifying a target user associated with a facial signature in a database based at least in part on a statistical correlation between a detected facial signature in the digital image and one or more facial signatures in the database;

extracting a profile of the target user from a database, wherein the profile comprises one or more privacy preferences; and

generating a customized profile of the target user, wherein the customized profile omits one or more elements of the profile of the target user based on the one or more privacy preferences.

2. The method of claim 1, wherein the received input is received from a sensor device, wherein the sensor device captures the digital image.

3. The method of claim 1, further comprising:

transmitting the customized profile of the target user to a user device.

4. The method of claim 1, wherein detecting the facial signature comprises categorizing a facial expression pattern of the face of the digital image, wherein the facial expression pattern comprises one or more of a smile, frown, gender, and age.

5. The method of claim 1, wherein detecting the facial signature comprises categorizing an image context from the digital image, wherein the image context comprises one or more of a location, time, angle, color, and lighting.

6. The method of claim 1, wherein the one or more privacy preferences elect to omit the one or elements of the profile of the target user based on one or more of:

a location of a sensor device capturing the digital image;

a location of a device associated with the target user;

a location the digital image is captured;

a time the digital image is captured;

a time the digital image is received;

a facial expression pattern of the face of the digital image; and

an identity of a user associated with the sensor device.

7. The method of claim 1, wherein the one or more elements of the profile of the target user comprise one or more of the following:

a name, present location, a residence location, work location, age, gender, birthday, job history, education history, associated social media users, and images associated with the target user.

8. The method of claim 1, wherein the digital image comprises one or more of:

a digital photograph; and

a digital video.

9. A computer program product for controlling privacy on a computer, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer to cause the computer to perform a method comprising:

receiving, by the computer, an input including a face recognition query and a digital image of a face;

identifying, by the computer, a target user associated with a facial signature in a database based at least in part on a statistical correlation between a detected facial signature in the digital image and one or more facial signatures in the database;

extracting, by the computer, a profile of the target user from a database, wherein the profile comprises one or more privacy preferences; and

generating, by the computer, a customized profile of the target user, wherein the customized profile omits one or more elements of the profile of the target user based on the one or more privacy preferences.

10. The computer program product of claim 9, wherein the received input is received from a sensor user, wherein the sensor user captures the digital image with a sensor device.

11. The computer program product of claim 9, further comprising:

detecting, by the computer, the facial signature from the digital image of the face;

calculating, by the computer, the statistical correlation between the detected facial signature and the facial signature in the first database; and

transmitting the customized profile of the target user to a sensor user.

12. The computer program product of claim 9, wherein detecting the facial signature comprises categorizing a facial expression pattern from the face of the digital image, wherein the facial expression pattern comprises one or more of a smile, frown, gender, and age.

13. The computer program product of claim 9, wherein detecting the facial signature comprises categorizing an image context from the digital image, wherein the image context comprises one or more of a location, time, angle, color, and lighting.

14. The computer program product of claim 9, wherein the one or more privacy preferences elect to omit the one or elements of the profile of the target user based on one or more of:

a location of a sensor device capturing the digital image;

a location of a device associated with the target user;

a location the digital image is captured;

a time the digital image is captured;

a time the digital image is received;

a facial expression pattern of the face of the digital image; and

an identity of a user associated with the sensor device.

15. The computer program product of claim 9, wherein the one or more elements of the profile of the target user comprise one or more of the following:

a name, present location, a residence location, work location, age, gender, birthday, job history, education history, associated social media users, and images associated with the target user.

16. A computer system for controlling privacy on a computer, the computer system comprising:

one or more computer processors;

one or more computer-readable storage media;

program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising instructions to;

receive, by the computer, an input including a face recognition query and a digital image of a face;

identify, by the computer, a target user associated with a facial signature in a database based at least in part on a statistical correlation between a detected facial signature in the digital image and one or more facial signatures in the database;

extract, by the computer, a profile of the target user from a database, wherein the profile comprises one or more privacy preferences; and

generate, by the computer, a customized profile of the target user, wherein the customized profile omits one or more elements of the profile of the target user based on the one or more privacy preferences.

17. The system of claim 16, wherein the instructions to identify the facial signature comprise categorizing a facial expression pattern from the face of the digital image, wherein the facial expression pattern comprises one or more of a smile, frown, gender, and age.

18. The system of claim 16, wherein detecting the facial signature comprises categorizing an image context from the digital image, wherein the image context comprises one or more of a location, time, angle, color, and lighting.

19. The system of claim 16, wherein the one or more privacy preferences elect to omit the one or elements of the profile of the target user based on one or more of:

a location of a sensor device capturing the digital image;

a location of a device associated with the target user;

a location the digital image is captured;

a time the digital image is captured;

a time the digital image is received;

a facial expression pattern of the face of the digital image; and

an identity of a user associated with the sensor device.

20. The system of claim 16, wherein the one or more elements of the profile of the target user comprise one or more of the following:

a name, present location, a residence location, work location, age, gender, birthday, job history, education history, associated social media users, and images associated with the target user.