# US 10,769,255 B2 · Methods and apparatuses for adaptively updating enrollment database for user authentication

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- Number: US 10,769,255 B2
- Document ID: US10769255B2
- Status: Granted
- Kind: B2
- Application number: 15/270,172
- Filed: 2016-09-20
- Published: 2017-05-11
- Granted: 2020-09-08
- Earliest claimed: 2015-11-11
- Assignees: Samsung Electronics Co., Ltd.
- Applicants: Samsung Electronics Co., Ltd.
- Inventors: Jungbae Kim; Seon Min Rhee; Jaejoon Han
- Web page: https://patentgrep.com/patent/US10769255B2

## CPC

- G06V 10/772: Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries
- G06F 16/23: Updating
- G06F 16/51: Indexing; Data structures therefor; Storage structures
- G06F 18/28: Determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries
- G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints
- G06F 21/36: by graphic or iconic representation
- G06F 21/45: Structures or tools for the administration of authentication
- G06V 40/1335: {Combining adjacent partial images (e.g. slices) to create a composite input or reference pattern; Tracking a sweeping finger movement}
- G06V 40/1365: {Matching; Classification}
- G06V 40/161: {Detection; Localisation; Normalisation}
- G06V 40/169: {Holistic features and representations, i.e. based on the facial image taken as a whole}
- G06V 40/172: {Classification, e.g. identification}
- G06V 40/174: {Facial expression recognition}
- G06V 40/50: Maintenance of biometric data or enrolment thereof
- G06V 40/70: Multimodal biometrics, e.g. combining information from different biometric modalities
- G07C 9/37: using biometric data, e.g. fingerprints, iris scans or voice recognition
- H04L 63/0861: {using biometrical features, e.g. fingerprint, retina-scan (cryptographic mechanisms or cryptographic arrangements for entity authentication using biological data H04L9/3231)}
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

A method of adaptively updating an enrollment database is disclosed. The method may include extracting a first feature vector from an input image, the input image including a face of a user, determining whether to enroll the input image in the enrollment database based on the first feature vector, second feature vectors of enrollment images and a representative vector, the second feature vectors of the enrollment images being enrolled in the enrollment database, and the representative vector representing the second feature vectors, and enrolling the input image in the enrollment database based on a result of the determining.

## Claims

### Claim 1

A method of adaptively updating an enrollment database, the method comprising:
extracting a first feature vector from an input image, the input image including a face of a user;
determining whether to enroll the input image in the enrollment database based on the first feature vector, second feature vectors of enrollment images and a representative vector, the second feature vectors of the enrollment images being enrolled in the enrollment database, and the representative vector representing the second feature vectors, the first feature vector being different than the second feature vectors and the representative vector, the determining whether to enroll the input image including,
(i) determining whether the input image is an outlier based on the first feature vector and the representative vector, and
(ii) determining whether a feature range of the enrollment database is increased based on the first feature vector and the second feature vectors; and
enrolling the input image in the enrollment database based on a result of the determining.

### Claim 2 (depends on 1)

The method of claim 1, wherein the determining of whether to enroll the input image comprises:
determining whether the input image is the outlier based on the first feature vector, the second feature vectors, and the representative vector, the determining whether the input image is the outlier includes,
calculating a minimum distance between the first feature vector and the second feature vectors,
calculating a representative distance between the first feature vector and the representative vector, and
determining that the input image is the outlier based on the minimum distance and the representative distance.

### Claim 3 (depends on 2)

The method of claim 2, wherein the determining that the input image is the outlier determines that the input image is the outlier based on whether the minimum distance is less than a first threshold and whether the representative distance is less than a second threshold.

### Claim 4 (depends on 1)

The method of claim 1, wherein the determining whether to enroll the input image comprises:
determining whether the feature range of the enrollment database is increased based on the first feature vector and the second feature vectors, the determining whether the feature range of the enrollment database is extended includes,
determining an accumulation feature distance corresponding to each vector in a vector set, the vector set including the first feature vector and the second feature vectors, the accumulation feature distance determined based on distances between the corresponding vector and remaining vectors in the vector set, and
determining whether the accumulation feature distance corresponding to the first feature vector is greater than at least one of the accumulation feature distances corresponding to the second feature vectors.

### Claim 5 (depends on 4)

The method of claim 4, wherein the enrolling the input image in the enrollment database comprises:
replacing one of the enrollment images with the input image if the accumulation feature distance corresponding to the first feature vector is greater than the at least one of the accumulation feature distances corresponding to the second feature vectors.

### Claim 6 (depends on 5)

The method of claim 5, wherein the replacing the one of the enrollment images replaces the enrollment image corresponding to the second feature vector having a minimum accumulation feature distance among the accumulation feature distances.

### Claim 7 (depends on 1)

The method of claim 1, wherein the determining whether to enroll the input image comprises:
comparing a number of the enrollment images enrolled in the enrollment database to a maximum enrollment number of the enrollment database.

### Claim 8 (depends on 7)

The method of claim 7, wherein the enrolling the input image in the enrollment database comprises:
adding the input image to the enrollment database if the number of the enrollment images is less than the maximum enrollment number; and
replacing one of the enrollment images enrolled in the enrollment database with the input image if the number of the enrollment images is equal to the maximum enrollment number.

### Claim 9 (depends on 8)

The method of claim 8, wherein the adding the input image to the enrollment database adds the input image to the enrollment database if the input image is not an outlier and the number of the enrollment images is less than the maximum enrollment number.

### Claim 10 (depends on 1)

The method of claim 1, wherein the determining whether to enroll the input image comprises:
authenticating the user based on the first feature vector, the second feature vectors, and the representative vector.

### Claim 11 (depends on 10)

The method of claim 10, wherein the authenticating the user comprises:
calculating a minimum distance between the first feature vector and the second feature vectors;
calculating a representative distance between the first feature vector and the representative vector; and
authenticating the user based on the minimum distance, the representative distance and at least one distance threshold.

### Claim 12 (depends on 10)

The method of claim 10, wherein the determining whether to enroll the input image determines whether to enroll input image in the enrollment database based on the authenticating the user.

### Claim 13 (depends on 1)

The method of claim 1, further comprising:
updating the representative vector based on the first feature vector if the input image is enrolled in the enrollment database.

### Claim 14

A non-transitory computer-readable medium comprising program code that, when executed by a processor, causes the processor to perform
extracting a first feature vector from an input image, the input image including a face of a user;
determining whether to enroll the input image in an enrollment database based on the first feature vector, second feature vectors of enrollment images and a representative vector, the second feature vectors of the enrollment images being enrolled in the enrollment database, and the representative vector representing the second feature vectors, the first feature vector being different than the second feature vectors and the representative vector, the determining whether to enroll the input image including,
(i) determining whether the input image is an outlier based on the first feature vector and the representative vector, and
(ii) determining whether a feature range of the enrollment database is increased based on the first feature vector and the second feature vectors; and
enrolling the input image in the enrollment database based on a result of the determining.

### Claim 15

An adaptive updating apparatus of an enrollment database, the adaptive updating apparatus comprising:
a memory configured to store the enrollment database and storing computer-readable instructions; and
one or more processors configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
extract a first feature vector from an input image, the input image including a face of a user, and
enroll the input image by determining whether to enroll the input image in the enrollment database based on (i) whether the input image is an outlier based on the first feature vector and a representative vector and (ii) whether a feature range of the enrollment database is increased based on the first feature vector and second feature vectors of enrollment images, the second vectors being enrolled in the enrollment database, the representative vector representing the second feature vectors, and the first feature vector being different than the second feature vectors and the representative vector.

### Claim 16 (depends on 15)

The adaptive updating apparatus of claim 15, wherein the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
calculate a minimum distance between the first feature vector and the second feature vectors,
calculate a representative distance between the first feature vector and the representative vector, and
determine whether the input image is the outlier based on the minimum distance and the representative distance.

### Claim 17 (depends on 15)

The adaptive updating apparatus of claim 15, wherein the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
determine an accumulation feature distance corresponding to each vector in a vector set based on distances between the corresponding vector and remaining vectors in the vector set, the vector set including the first feature vector and the second feature vectors, and
determine whether a feature range of the enrollment database is extended based on whether the accumulation feature distance corresponding to the first feature vector is greater than at least one of the accumulation feature distances corresponding to the second feature vectors.

### Claim 18 (depends on 17)

The adaptive updating apparatus of claim 17, wherein the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
replace the enrollment image corresponding to the second feature vector having a minimum accumulation feature distance among the enrollment images with the input image if the accumulation feature distance corresponding to the first feature vector is greater than the at least one of the accumulation feature distances corresponding to the second feature vectors.

### Claim 19 (depends on 15)

The adaptive updating apparatus of claim 15, wherein the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
determine whether to add the input image or to replace one of the enrollment images in the enrollment database based on a number of the enrollment images enrolled in the enrollment database and a maximum enrollment number of the enrollment database.

### Claim 20 (depends on 15)

The adaptive updating apparatus of claim 15, wherein the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
authenticate the user based on the first feature vector, the second feature vectors, and the representative vector, and
determine whether to enroll the input image in the enrollment database based on the authenticating the user.

### Claim 21 (depends on 15)

The adaptive updating apparatus of claim 15, wherein the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to update the representative vector using the first feature vector if the input image is enrolled in the enrollment database.

### Claim 22

An adaptive updating apparatus of an enrollment database, the adaptive updating apparatus comprising:
a memory storing computer-readable instructions; and
one or more processors configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
authenticate an input image based on the enrollment database,
determine whether the input image is an outlier based on a representative vector, the representative vector representing enrollment images in the enrollment database,
determine, in response to determining the input image is not an outlier, whether a feature range of the enrollment database is increased based on a first feature vector of the input image and second feature vectors of the enrollment images, the first feature vector being different than the second feature vectors and the representative vector, and
adaptively update the enrollment database based on a result of the determining whether the feature range of the enrollment database is increase.

### Claim 23 (depends on 22)

The apparatus of claim 22, wherein, to determine whether the input image is the outlier, the one or more processors is configured to execute the computer-readable instructions such that the one or more processors is configured to cause the adaptive updating apparatus to,
calculate a minimum distance between the first feature vector and the second feature vectors, the first feature vector extracted from the input image and the second feature vectors extracted from the enrollment images in the enrolment database,
calculate a representative distance between the first feature vector and the representative vector, and
determine whether a first condition associated with the minimum distance and a second condition associated with the representative distance are satisfied.