IP Library Granted Patent US 11,755,709
Granted Patent B2
US 11,755,709 · App. 17/676,797 · Granted Sep 12, 2023

Artificial intelligence-based generation of anthropomorphic signatures and use thereof

Inventors: Axel Sly (Palo Alto, CA); Srivatsa Akshay Sharma (Santa Clara, CA); Brett Robert Redinger (Oakland, CA); Devin Daniel Reich (Olympia, WA); Geert Trooskens (Meise, BE); Meelis Lootus (London, GB); Young Jin Lee (Vancouver, CA); Ricardo Lopez Arredondo (Schertz, TX); Frederick Franklin Kautz, IV (Fremont, CA); Satish Srinivasan Bhat (Fremont, CA); Scott Michael Kirk (Belmont, CA); Walter Adolf De Brouwer (Los Altos Hills, CA); Kartik Thakore (Santa Clara, CA)
Assignee: SHARECARE AI, INC.
G06F21/32G06F18/214G06F21/45G06K7/1417G06K19/06037G06N5/04G06N20/00G06V10/451G06V10/761G06V10/774G06V10/7715G06V10/803G06V40/161G06V40/168G06V40/70G16H10/60H04L9/085H04L9/0841H04L9/0866H04L9/0894H04L9/3228H04L9/3231H04L9/3236H04L9/3239H04L9/3242H04L9/3247H04L9/3297G06N3/04G06N3/08H04L63/0861
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Quick Facts
Patent No.
US 11,755,709
App. No.
17/676,797
Granted
Sep 12, 2023
Kind
B2
Abstract

The technology disclosed relates to authenticating users using a plurality of non-deterministic registration biometric inputs. During registration, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate sets of feature vectors. The non-deterministic biometric inputs can include a plurality of face images and a plurality of voice samples of a user. A characteristic identity vector for the user can be determined by averaging feature vectors. During authentication, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate a set of authentication feature vectors. The sets of feature vectors are projected onto a surface of a hyper-sphere. The system can authenticate the user when a cosine distance between the authentication feature vector and a characteristic identity vector for the user is less than a pre-determined threshold.

Claims (45)

1. A computer-implemented method of establishing authentication credentials using a plurality of non-deterministic registration biometric inputs, the method including:

feeding, during registration, the plurality of non-deterministic biometric inputs to a pre-trained machine learning model usable for a plurality of users and generating sets of feature vectors, wherein the non-deterministic biometric inputs include a plurality of face images and a plurality of voice samples of a user of the plurality of user;

projecting the sets of feature vectors onto a surface of a hyper-sphere;

computing a characteristic identity vector representing the user based on a user's set of the projected feature vectors; and

saving the characteristic identity vector for use during authentication of the user.

2. The method of claim 1 , further including registering a cryptographic signature of the characteristic identity vector with an identity server, accompanied by a photograph of the user selected from the plurality of face images.

3. The method of claim 1 , further including registering the characteristic identity vector with an identity server, accompanied by a photograph of the user that becomes one of the plurality of face images used to compute the characteristic identity vector.

4. The method of claim 1 , wherein the sets of feature vectors are projected onto a surface of a unit hyper-sphere.

5. The method of claim 1 , further including using one or more deterministic inputs to establish the authentication credentials, comprising:

feeding genomic data to a hash; and

using the hashed genomic data as at least one dimension of the characteristic identity vector.

6. The method of claim 1 , further including preprocessing the face image data to separate the face from background before generating the feature vectors.

7. The method of claim 1 , further including preprocessing the face image data by selecting individual frames from a video sequencing, wherein the individual frames are selected based on an image sharpness metric.

8. The method of claim 1 , further including preprocessing the voice data by selecting an audio segment corresponding to a phrase specified for the user to read.

9. A system including one or more processors coupled to memory, the memory loaded with computer instructions to establish authentication credentials using a plurality of non-deterministic registration biometric inputs, the instructions, when executed on the processors, implement actions comprising:

feeding, during registration, the plurality of non-deterministic biometric inputs to a pre-trained machine learning model usable for a plurality of users and generating sets of feature vectors, wherein the non-deterministic biometric inputs include a plurality of face images and a plurality of voice samples of a user of the plurality of users;

projecting the sets of feature vectors onto a surface of a hyper-sphere;

computing a characteristic identity vector representing the user based on a user's set of the projected feature vectors; and

saving the characteristic identity vector for use during authentication of the user.

10. The system of claim 9 , further implementing actions comprising:

registering a cryptographic signature of the characteristic identity vector with an identity server, accompanied by a photograph of the user selected from the plurality of face images.

11. The system of claim 9 , further implementing actions comprising:

registering the characteristic identity vector with an identity server, accompanied by a photograph of the user that becomes one of the plurality of face images used to compute the characteristic identity vector.

12. The system of claim 9 , wherein the sets of feature vectors are projected onto a surface of a unit hyper-sphere.

13. The system of claim 9 , further implementing actions comprising:

using one or more deterministic inputs to establish the authentication credentials, comprising:

feeding genomic data to a hash; and

using the hashed genomic data as at least one dimension of the characteristic identity vector.

14. The system of claim 9 , further implementing actions comprising:

preprocessing the face image data to separate the face from background before generating the feature vectors.

15. The system of claim 9 , further implementing actions comprising:

preprocessing the face image data by selecting individual frames from a video sequencing,

wherein the individual frames are selected based on an image sharpness metric.

16. The system of claim 9 , further implementing actions comprising:

preprocessing the voice data by selecting an audio segment corresponding to a phrase specified for the user to read.

17. A non-transitory computer readable storage medium impressed with computer program instructions to establish authentication credentials using a plurality of non-deterministic registration biometric inputs, the instructions, when executed on a processor, implement a method comprising:

feeding, during registration, the plurality of non-deterministic biometric inputs to a ore-trained machine learning model usable for a plurality of users and generating sets of feature vectors, wherein the non-deterministic biometric inputs include a plurality of face images and a plurality of voice samples of a user of the plurality of users;

projecting the sets of feature vectors onto a surface of a hyper-sphere;

computing a characteristic identity vector representing the user based on a user's set of the projected feature vectors; and

saving the characteristic identity vector for use during authentication of the user.

18. The non-transitory computer readable storage medium of claim 17 , implementing the method further comprising:

registering a cryptographic signature of the characteristic identity vector with an identity server, accompanied by a photograph of the user selected from the plurality of face images.

19. The non-transitory computer readable storage medium of claim 17 , implementing the method further comprising:

registering the characteristic identity vector with an identity server, accompanied by a photograph of the user that becomes one of the plurality of face images used to compute the characteristic identity vector.

20. The non-transitory computer readable storage medium of claim 17 , wherein the sets of feature vectors are projected onto a surface of a unit hyper-sphere.

Assignments (3)
SECURITY INTEREST Recorded Oct 22, 2024
From: HEALTHWAYS SC, LLC; SHARECARE AI, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION
Reel/Frame 068977/0210 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 22, 2022
From: SLY, AXEL; SHARMA, SRIVATSA AKSHAY; REDINGER, BRETT ROBERT; REICH, DEVIN DANIEL; TROOSKENS, GEERT; LOOTUS, MEELIS; LEE, YOUNG JIN; ARREDONDO, RICARDO LOPEZ; KAUTZ, FREDERICK FRANKLIN, IV; BHAT, SATISH SRINIVASAN; KIRK, SCOTT MICHAEL; DE BROUWER, WALTER ADOLF; THAKORE, KARTIK
To: DOC.AI, INC.
Reel/Frame 059063/0527 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 22, 2022
From: DOC.AI, INC.
To: SHARECARE AI, INC.
Reel/Frame 059063/0810 →
Continuity (3)
Continuation 17235871 · Apr 20, 2021
Provisional Application 63013536 · Apr 21, 2020
Related Publication 20220179943A1 · Jun 9, 2022