# US 2020/0401791 A1 · Methods and Systems for Dynamic and Incremental Face Recognition

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- Number: US 2020/0401791 A1
- Document ID: US20200401791A1
- Status: Published application
- Kind: A1
- Application number: 16/812,101
- Filed: 2020-03-06
- Published: 2020-12-24
- Earliest claimed: 2019-06-19
- Assignees: Samsung Electronics Co., Ltd.
- Applicants: Samsung Electronics Company, Ltd.
- Inventors: Jiang Gao; Xinyao Wang; Gene Becker
- Web page: https://patentgrep.com/patent/US20200401791A1

## CPC

- G06N 20/00: Machine learning
- G06V 10/764: using classification, e.g. of video objects
- G06V 10/768: {using context analysis, e.g. recognition aided by known co-occurring patterns}
- G06V 10/774: Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
- G06V 20/30: in albums, collections or shared content, e.g. social network photos or video
- G06V 40/166: {using acquisition arrangements}
- G06V 40/172: {Classification, e.g. identification}
- G06V 40/173: {face re-identification, e.g. recognising unknown faces across different face tracks}
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

In one embodiment, a method includes identifying a facial image from an image of a scene. The method then determines a context associated with the facial image based on a context model. The method then identifies a person from a database based on the context and a facial recognition model associated with the facial image.

## Claims

### Claim 1

A method comprising, by a computer device:
identifying a facial image from an image of a scene;
determining a context associated with the facial image based on a context model; and
identifying a person from a database based on the context and a facial recognition model associated with the facial image.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
determining an informativeness and a representativeness of the facial image; and
presenting the facial image to be labelled for training the facial recognition model.

### Claim 3 (depends on 2)

The method of claim 2, wherein presenting the facial image comprises presenting the context associated with the facial image.

### Claim 4 (depends on 1)

The method of claim 1, wherein the context comprises at least one of a visual consistency, a sequential order, a presence associated with the scene, or a coexistence pattern associated with the person or the scene.

### Claim 5 (depends on 4)

The method of claim 4, wherein the coexistence pattern associated with the person identifies a first person and a second person that have previously been identified together, and wherein the coexistence pattern of the scene comprises a first person identified in the scene and a set of scene parameters.

### Claim 6 (depends on 1)

The method of claim 1, wherein:
the scene comprises one or more scene parameters; and
the scene parameters comprise one or more of a time associated with the scene, a date associated with the scene, one or more elements captured within the scene, or an activity associated with the scene.

### Claim 7 (depends on 1)

The method of claim 1, wherein identifying the person from the database comprises determining the person is an unfamiliar person based on failing to match the facial image to one of a plurality of facial recognition models.

### Claim 8

An apparatus comprising:
a camera; and
one or more non-transitory storage media embodying instructions and one or more processors operable to execute the instructions to:
identify a facial image from an image of a scene;
determine a context associated with the facial image based on a context model; and
identify a person from a database based on the context and a facial recognition model associated with the facial image.

### Claim 9 (depends on 8)

The apparatus of claim 8, wherein the processors are further operable to execute the instructions to:
determine an informativeness and a representativeness of the facial image; and
present the facial image to be labelled for training the facial recognition model.

### Claim 10 (depends on 9)

The apparatus of claim 9, wherein the processors are further operable to execute the instructions to present the context associated with the facial image.

### Claim 11 (depends on 8)

The apparatus of claim 8, wherein the context comprises at least one of a visual consistency, a sequential order, a presence associated with the scene, or a coexistence pattern associated with the person or the scene.

### Claim 12 (depends on 11)

The apparatus of claim 11, wherein the coexistence pattern associated with the person identifies a first person and a second person that have previously been identified together, and wherein the coexistence pattern of the scene comprises a first person identified in the scene and a set of scene parameters

### Claim 13 (depends on 8)

The apparatus of claim 8, wherein:
the scene comprises one or more scene parameters; and
the scene parameters comprise one or more of a time associated with the scene, a date associated with the scene, one or more elements captured within the scene, or an activity associated with the scene.

### Claim 14 (depends on 8)

The apparatus of claim 8, wherein identifying the person from the database comprises determining the person is an unfamiliar person based on failing to match the facial image to one of a plurality of facial recognition models.

### Claim 15

One or more non-transitory computer-readable storage media embodying instructions that when executed by one or more processors cause the one or more processors to:
identify a facial image from an image of a scene;
determine a context associated with the facial image based on a context model; and
identify a person from a database based on the context and a facial recognition model associated with the facial image.

### Claim 16 (depends on 15)

The media of claim 15, further embodying instructions that when executed cause the one or more processors to:
determine an informativeness and a representativeness of the facial image; and
present the facial image to be labelled for training the facial recognition model.

### Claim 17 (depends on 16)

The media of claim 16, further embodying instructions that when executed cause the one or more processors to present the context associated with the facial image.

### Claim 18 (depends on 15)

The media of claim 15, wherein the context comprises at least one of a visual consistency, a sequential order, a presence associated with the scene, or a coexistence pattern associated with the person or the scene.

### Claim 19 (depends on 18)

The media of claim 18, wherein the coexistence pattern associated with the person identifies a first person and a second person that have previously been identified together, and wherein the coexistence pattern of the scene comprises a first person identified in the scene and a set of scene parameters

### Claim 20 (depends on 15)

The media of claim 15, wherein:
the scene comprises one or more scene parameters; and
the scene parameters comprise one or more of a time associated with the scene, a date associated with the scene, one or more elements captured within the scene, or an activity associated with the scene.