Identifying objects within images from different sources

Patent metadata

Field	Value
Publication number	US-11710348-B2
Application number	US-202217949876-A
Country	US
Kind code	B2
Filing date	Sep 21, 2022
Priority date	Jun 3, 2020
Publication date	Jul 25, 2023
Grant date	Jul 25, 2023

Abstract

Techniques are disclosed for providing a notification that a person is at a particular location. For example, a resident device may receive from a user device an image that shows a face of a first person, the image being captured by a first camera of the user device. The resident device may also receive, from another device having a second camera, a second image showing a portion of a face of a second person, the second camera having a viewable area showing a particular location. The resident device may determine a score indicating a level of similarity between a first set of characteristics associated with the face of the first person and a second set of characteristics associated with the face of a second person. The resident device may then provide to the user device a notification based on determining the score.

First claim

What is claimed is:

1. A computer-implemented method, comprising:
receiving, by a resident device from a first device, an image cropping generated from an image of a plurality of images accessible by the first device, the image cropping comprising a portion of a face of a first person, the plurality of images captured by a first camera of the first device;
receiving, by the resident device and from another device comprising a second camera, a second image comprising a portion of a face of a second person, the second camera having a viewable area comprising a particular location associated with the resident device;
receiving, by the resident device and from a second device, a second image cropping generated from a library of images accessible by the second device, the second image cropping showing a second portion of the face of the first person;
including, by the resident device, the second image cropping within a plurality of image croppings to produce an updated reference set of image croppings, the updated reference set of image croppings including both the image cropping from the first device and the second image cropping from the second device; and
generating, by a trained model of the first device, a faceprint for the face of the first person based at least in part on the updated reference set of image croppings.

2. The computer-implemented method of claim 1 , wherein the plurality of images is managed as part of the library of images comprising contacts associated with the first device, and further comprising:
determining a score that corresponds to a level of similarity between a first set of characteristics associated with the faceprint of the first person and a second set of characteristics associated with the face of the second person;
determining whether the first person is the second person based at least in part on the score; and
providing to the first device a notification based at least in part on the determination.

3. The computer-implemented method of claim 2 , wherein the image is associated with a first level of image quality and the second image is associated with a second level of image quality that is different from the first level of image quality.

4. The computer-implemented method of claim 2 , wherein determining the score further comprises:
generating, by a trained model of the resident device, a first faceprint of the face of the first person based at least in part on the image cropping, the first faceprint corresponding to a multidimensional vector, a dimension of the vector associated with a characteristic of the first set of characteristics of the face of the first person.

5. The computer-implemented method of claim 2 , further comprising:
determining, by the resident device, that the first person is the second person based at least in part on the score; and
determining, by the resident device, not to provide the notification to the first device based at least in part on determining that the first person is the second person.

6. The computer-implemented method of claim 2 , further comprising:
determining, by the resident device, that the first person is not the second person based at least in part on the score; and
providing, by the resident device and to the first device, the notification that indicates that the second person is not a contact associated with the first device.

7. The computer-implemented method of claim 2 , further comprising:
maintaining, by the resident device, a face quality metric that indicates a level of quality associated with the second set of characteristics associated with the face of the second person, the face quality metric operable for determining whether a particular face of a person is recognizable or unrecognizable; and
determining, by the resident device, that the face of the second person is recognizable based at least in part determining that the level of quality indicated by the face quality metric matches a threshold; and
determining, by the resident device, whether the first person is the second person based at least in part on determining that the face of the second person is recognizable.

8. A first device, comprising:
a memory configured to store computer-executable instructions; and
one or more processors in communication with the memory and configured to access the memory and execute the computer-executable instructions to, at least:
receive from a first device an image cropping generated from an image of a plurality of images accessible by the first device, the image cropping comprising a portion of a face of a first person, the plurality of images captured by a first camera of the first device;
receive from another device comprising a second camera, a second image comprising a portion of a face of a second person, the second camera having a viewable area comprising a particular location associated with the first device;
receive, from a second device, a second image cropping generated from a library of images accessible by the second device, the second image cropping showing a second portion of the face of the first person;
include the second image cropping within a plurality of image croppings to produce an updated reference set of image croppings, the updated reference set of image croppings including both the image cropping from the first device and the second image cropping from the second device; and
generate, by a trained model of the first device, a faceprint for the face of the first person based at least in part on the updated reference set of image croppings.

9. The first device of claim 8 , wherein the plurality of images, respectively, comprises a particular portion of the face of the first person, the image being one of a subset of the plurality of images, the image included in the subset based at least in part on an information gain associated with the portion of the face of the first person, the information gain used to perform a facial recognition of the face of the first person.

10. The first device of claim 9 , wherein the image cropping is one of a plurality of image croppings that are received by the first device from the first device, the plurality of image croppings respectively generated from the subset of the plurality of images and operable as a reference set of image croppings.

11. The first device of claim 10 , wherein the instructions to determine the score comprise additional instructions to:
generate, by a trained model of the first device, a first faceprint of the face of the first person based at least in part on the plurality of image croppings; and
compare, by the trained model of the first device, the first faceprint with the second set of characteristics associated with the face of the second person.

12. The first device of claim 11 , wherein the instructions to compare the first faceprint with the second set of characteristics associated with the face of the second person comprise additional instructions to:
generate, by the trained model, a second faceprint of the face of the second person based at least in part on the second image, the second faceprint associated with the second set of characteristics; and
determine, by the trained model, a level of similarity between the first faceprint and the second faceprint.

13. The first device of claim 8 , wherein the one or more processors further execute the instructions to:
determine a score that corresponds to a level of similarity between a first set of characteristics associated with the faceprint of the first person and a second set of characteristics associated with the face of the second person;
determine whether the first person is the second person based at

Assignees

• Apple Inc

Inventors

• Dahlkamp Hendrik
• Sharma Vinay
• Gupta Nitin
• Chabert Floris
• Edwards Andrew C
• Williams Mitchell
• Jin Jonghoon
• Fraioli Nicholas M
• Krishnan Aravindhan K
• Coffman Patrick L

Classifications

• G06V40/172 Primary

  Classification, e.g. identification · CPC title

• G06F18/22

  Matching criteria, e.g. proximity measures · CPC title

• G06F21/602

  Providing cryptographic facilities or services · CPC title

• G06T7/11

  Region-based segmentation · CPC title

• G06V40/50

  Maintenance of biometric data or enrolment thereof · CPC title