IP Library Granted Patent US 11,263,438
Granted Patent B2
US 11,263,438 · App. 16/709,105 · Granted Mar 1, 2022

Augmented reality identity verification

Inventor: Adrian Kaehler (Los Angeles, CA)
Assignee: Magic Leap, Inc.
G06K9/00288G06K9/00281G06K9/00456G06K9/6215G06K9/6257G06T19/006
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Quick Facts
Patent No.
US 11,263,438
App. No.
16/709,105
Granted
Mar 1, 2022
Kind
B2
Abstract

An augmented reality device (ARD) can present virtual content which can provide enhanced experiences with the user's physical environment. For example, the ARD can detect a linkage between a person in the FOV of the ARD and a physical object (e.g., a document presented by the person) or detect linkages between the documents. The linkages may be used in identity verification or document verification.

Claims (47)

1. A method for determining a linkage between a person and a plurality of documents using an augmented reality (AR) system, the method comprising:

under control of the AR system comprising computer hardware, the AR system comprising an outward-facing camera configured to image an environment and an optical sensor configured to emit light outside of a visible spectrum of a human:

obtaining an image of the environment;

detecting a person, a first document and a second document in the image;

extracting first personal information based at least partly on an analysis of the image of the first document;

extracting second personal information from the second document;

extracting third personal information of the person based at least partly on an analysis of the image of the person;

determining a linkage between two or more of the person, the first document, and the second document based on a match between extracted information in a same category of information from the first personal information, the second personal information, and the third personal information, respectively.

2. The method of claim 1 , wherein the light emitted by the optical sensor comprises ultraviolet light.

3. The method of claim 1 , wherein the category of information comprises a name, an address, an expiration date, a picture of a person, a fingerprint, an iris code, a height, a gender, a hair color, an eye color, or a weight.

4. The method of claim 1 , wherein extracting the first personal information and extracting the third personal information comprise:

detecting a first face in the image, wherein the first face is included in the first document;

detecting a second face in the image, wherein the second face is associated with the person in the environment;

identifying first facial features associated with the first face; and

identifying second facial features associated with the second face.

5. The method of claim 4 , wherein detecting the first face or detecting the second face comprises locating the first face or the second face in the image using at least one of the following: a wavelet-based boosted cascade algorithm or a deep neural network algorithm.

6. The method of claim 4 , wherein detecting the first face comprising:

analyzing movements of the first face; and

detecting the first face in response to a determination that the movements of the first face is described by a single planar homography.

7. The method of claim 4 , wherein identifying the first facial features or identifying the second facial features comprises calculating a first feature vector associated with the first face based at least partly on the first facial features or calculating a second feature vector associated with the second face based at least partly on the second facial features, respectively.

8. The method of claim 7 , further comprising assigning first weights to the first facial features based at least partly on locations of the respective first facial features, or assigning second weights to second facial features based at least partly on locations of the respective second facial features.

9. The method of claim 7 , wherein calculating the first feature vector or calculating the second feature vector is implemented using one or more of the following: a facial landmark detection algorithm, a deep neural network algorithm, or a template matching algorithm.

10. The method of claim 7 , comprising:

calculating a distance between the first feature vector and the second feature vector;

comparing the distance to a threshold value; and

confirming a match between the first face in the first document and the second face in the image when the distance passes the threshold value.

11. The method of claim 10 , wherein the distance is Euclidean distance.

12. The method of claim 1 , wherein the second personal information is invisible when illuminated with light within the Human Visible Spectrum.

13. The method of claim 12 , wherein extracting the second personal information comprises:

emitting light, by the optical sensor, onto the second document, wherein at least a portion of the light is outside of the HVS; and

identifying the second personal information under the light emitted by the optical sensor, wherein the second personal information is not directly visible to the human under a normal optical condition.

14. The method of claim 1 , wherein extracting the second personal information comprises:

identifying a label in the second document, wherein the label contains a reference to another data source; and

communicating with the other data source to retrieve the second personal information.

15. The method of claim 14 , wherein the label comprises one or more of the following: a quick response code or a bar code.

16. The method of claim 1 , comprising:

comparing the first personal information and the second personal information;

calculating a confidence score based at least in part on similarities or dissimilarities between the first personal information and the second personal information; and

detecting a match between the first personal information and the second personal information when the confidence score passes a threshold value.

17. The method of claim 1 , further comprising: flagging at least one of the first document or the second document as valid based at least partly on the detected match.

18. The method of claim 1 , further comprising:

in response to a determination that the match between extracted information in the same category of information does not exist from at least two of: the first personal information,

the second personal information, and the third personal information; and

providing an indication showing that the match does not exist.

19. The method of claim 18 , further comprising: searching in the environment, a fourth document comprising information that comprises a match to at least one of: the first personal information, the second personal information, or the third personal information.

20. The method of claim 1 , wherein the first document or the second document comprises: an identification document or an airline ticket.

21. The method of claim 1 , wherein detecting the person, the first document and the second document in the image comprises: identifying the person, the first document, or the second document based at least partly on a filter.

Assignments (2)
SECURITY INTEREST Recorded May 24, 2022
From: MOLECULAR IMPRINTS, INC.; MENTOR ACQUISITION ONE, LLC; MAGIC LEAP, INC.
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 060338/0665 →
PROPRIETARY INFORMATION AND INVENTIONS AGREEMENT Recorded Jul 28, 2021
From: KAEHLER, ADRIAN
To: MAGIC LEAP, INC.
Reel/Frame 057013/0782 →