IP Library Granted Patent US 10,319,130
Granted Patent B2
US 10,319,130 · App. 15/583,286 · Granted Jun 11, 2019

Anonymization of facial images

Inventors: Jacob Whitehill (Cambridge, MA); Javier R. Movellan (La Jolla, CO); Ian Fasel (San Diego, CA)
Assignee: Emotient, Inc.
G06T11/60G06K9/00228G06K9/00268G06K9/00302G06K9/00308G06T3/00G06T11/00H04N19/20G06K2009/00953
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Quick Facts
Patent No.
US 10,319,130
App. No.
15/583,286
Granted
Jun 11, 2019
Kind
B2
Abstract

A method facilitates the use of facial images through anonymization of facial images, thereby allowing people to submit their own facial images without divulging their identities. Original facial images are accessed and perturbed to generate synthesized facial images. Personal identities contained in the original facial images are no longer discernable from the synthesized facial images. At the same time, each synthesized facial image preserves at least some of the original attributes of the corresponding original facial image.

Claims (34)

1. A computer-implemented method for generating synthesized facial images, the method comprising:

receiving an image;

determining the image is the original facial image by detecting a face of a live human subject in the image;

receiving a preselected attribute reflected in facial images;

determining the original facial image has the preselected attribute; and

perturbing the original facial image to generate a synthesized facial image, the synthesized facial image no longer recognizable as the live human subject but preserving at least part of the preselected attribute of the original facial image.

2. The computer-implemented method of claim 1 , wherein the synthesized facial image is no longer recognizable as the live human subject when a mutual information between a personal identity of the live human subject and the synthesized facial image falls below a threshold.

3. The computer-implemented method of claim 1 , wherein the synthesized facial image is no longer recognizable as the live human subject when a probability that humans can correctly identify the live human subject from the synthesized facial image is no greater than a threshold.

4. The computer-implemented method of claim 1 , wherein the facial image is captured under additional circumstances that probe for the preselected attribute.

5. The computer-implemented method of claim 1 , wherein the preselected attribute comprises at least a facial expression or emotional expression.

6. The computer-implemented method of claim 1 , further comprising outputting for presentation the synthesized facial image that is no longer recognizable as the live human subject.

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

receive an image;

determine the image is the original facial image by detecting a face of a live human subject in the image;

receive a preselected attribute reflected in facial images;

determine the original facial image has the preselected attribute; and

perturb the original facial image to generate a synthesized facial image, the synthesized facial image no longer recognizable as the live human subject but preserving at least part of the preselected attribute of the original facial image.

8. The non-transitory computer readable medium of claim 7 , wherein the synthesized facial image is no longer recognizable as the live human subject when a mutual information between a personal identity of the live human subject and the synthesized facial image falls below a threshold.

9. The non-transitory computer readable medium of claim 7 , wherein the synthesized facial image is no longer recognizable as the live human subject when a probability that humans can correctly identify the live human subject from the synthesized facial image is no greater than a threshold.

10. The non-transitory computer readable medium of claim 7 , wherein the facial image is captured under additional circumstances that probe for the preselected attribute.

11. The non-transitory computer readable medium of claim 7 , wherein the preselected attribute comprises at least a facial expression or emotional expression.

12. The non-transitory computer readable medium of claim 7 , wherein the computer readable medium containing instructions that further cause the processor to output for presentation the synthesized facial image that is no longer recognizable as the live human subject.

13. A system for generating synthesized facial images, the system comprising:

a processor; and

a memory coupled to the processor and comprising instructions which, when executed by the processor, cause the system to:

receive an image;

determine the image is the original facial image by detecting a face of a live human subject in the image;

receive a preselected attribute reflected in facial images;

determine the original facial image has the preselected attribute; and

perturb the original facial image to generate a synthesized facial image, the synthesized facial image no longer recognizable as the live human subject but preserving at least part of the preselected attribute of the original facial image.

14. The system of claim 13 , wherein the synthesized facial image is no longer recognizable as the live human subject when a mutual information between a personal identity of the live human subject and the synthesized facial image falls below a threshold.

15. The system of claim 13 , wherein the synthesized facial image is no longer recognizable as the live human subject when a probability that humans can correctly identify the live human subject from the synthesized facial image is no greater than a threshold.

16. The system of claim 13 , wherein the facial image is captured under additional circumstances that probe for the preselected attribute.

17. The system of claim 13 , wherein the preselected attribute comprises at least a facial expression or emotional expression.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 21, 2021
From: EMOTIENT, INC.
To: APPLE INC.
Reel/Frame 056310/0823 →
Continuity (3)
Continuation 14802674 · Jul 17, 2015
Continuation In Part 13886193 · May 2, 2013
Related Publication 20170301121A1 · Oct 19, 2017