IP Library Granted Patent US 11,544,711
Granted Patent B2
US 11,544,711 · App. 16/719,807 · Granted Jan 3, 2023

Biometric feature database establishing method and apparatus

Inventors: Fen Zhai (Shanghai, CN); Chunlei Gu (Shanghai, CN); Lei Lu (Shanghai, CN); Yanghui Liu (Shanghai, CN)
Assignee: Advanced New Technologies Co., Ltd.
G06Q20/40145G06F7/08G06F16/51G06F16/5838G06V40/172G06V40/50H04L63/0861
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Quick Facts
Patent No.
US 11,544,711
App. No.
16/719,807
Granted
Jan 3, 2023
Kind
B2
Abstract

A usage frequency attribute is determined for each biometric feature in a biometric feature database. The usage frequency attribute indicates a matching success frequency of matching the biometric feature to a user having the biometric feature. The biometric features of the user are sorted in descending order of the usage frequency attribute. The sorting is based on a descending order of the usage frequency attributes for a given user. The biometric features in the biometric feature database are stored in descending order. The storing includes providing prioritized access to the biometric feature having a highest value of the usage frequency attribute so that the biometric feature is selected first in response to a request for the biometric feature of the user.

Claims (67)

1. A computer-implemented method, comprising:

determining, for each type of biometric identification of a plurality of different types of biometric identification, a frequency with which a type of biometric identification is successful in matching a corresponding biometric feature of a user that is associated with the type of biometric identification;

sorting, in descending order and as sorted biometric features, corresponding biometric features according to the frequency with which the plurality of different types of biometric identification that are associated with the corresponding biometric features are successful in matching corresponding biometric features of the user;

prioritizing access in a biometric feature database and to a particular biometric feature having a highest value of frequency of successful matching of the particular biometric feature by storing, in descending order and in the biometric feature database, the sorted biometric features, wherein biometric features that are associated with types of biometric identification that have a higher frequency of successful matching are stored, with respect to descending order, at a higher value in the biometric feature database when compared to biometric features that are associated with types of biometric information that have a lower frequency of successful matching;

obtaining a verification code that is allocated to the user;

generating a hash value corresponding to the verification code by performing a hash function calculation on the verification code;

identifying, as an identified biometric feature database, the biometric feature database based on the hash value corresponding to the verification code; and

performing biometric identification based on the identified biometric feature database and the sorted biometric features.

2. The computer-implemented method of claim 1 , wherein the frequency is a mathematical function of at least one of a number of times that a first biometric feature of the biometric features has been requested or a most recent usage time that the first biometric feature was matched.

3. The computer-implemented method of claim 1 , wherein sorting the biometric features comprises:

performing a weighted summation on at least two frequencies for a first biometric feature of the biometric features to obtain a frequency value; and

sorting the biometric features based on the weighted summation.

4. The computer-implemented method of claim 1 , comprising:

comparing a given biometric feature of the user with a given biometric feature in the identified biometric feature database;

updating, as an updated frequency, a frequency of the given biometric feature in the identified biometric feature database when a match is determined based on comparing the given biometric feature of the user with the given biometric feature in the identified biometric feature database; and

rearranging the biometric features in the identified biometric feature database based on the updated frequency.

5. The computer-implemented method of claim 1 , wherein the biometric features comprise a facial feature.

6. The computer-implemented method of claim 5 , comprising:

obtaining, as an obtained user facial feature, a user facial feature of the user;

comparing the obtained user facial feature with the biometric features in the identified biometric feature database; and

when a matched facial feature is obtained, performing a payment by using a payment account corresponding to the facial feature.

7. The computer-implemented method of claim 6 , wherein the obtained user facial feature of the user is compared with the biometric features in the identified biometric feature database based on feature ranks, wherein feature ranks are obtained after the biometric features in the identified biometric feature database are sorted.

8. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations, comprising:

determining, for each type of biometric identification of a plurality of different types of biometric identification, a frequency with which a type of biometric identification is successful in matching a corresponding biometric feature of a user that is associated with the type of biometric identification;

sorting, in descending order and as sorted biometric features, corresponding biometric features according to the frequency with which the plurality of different types of biometric identification that are associated with the corresponding biometric features are successful in matching corresponding biometric features of the user;

prioritizing access in a biometric feature database and to a particular biometric feature having a highest value of frequency of successful matching of the particular biometric feature by storing, in descending order and in the biometric feature database, the sorted biometric features, wherein biometric features that are associated with types of biometric identification that have a higher frequency of successful matching are stored, with respect to descending order, at a higher value in the biometric feature database when compared to biometric features that are associated with types of biometric information that have a lower frequency of successful matching;

obtaining a verification code that is allocated to the user;

generating a hash value corresponding to the verification code by performing a hash function calculation on the verification code;

identifying, as an identified biometric feature database, the biometric feature database based on the hash value corresponding to the verification code; and

performing biometric identification based on the identified biometric feature database and the sorted biometric features.

9. The non-transitory, computer-readable medium of claim 8 , wherein the frequency is a mathematical function of at least one of a number of times that a first biometric feature of the biometric features has been requested or a most recent usage time that the first biometric feature was matched.

10. The non-transitory, computer-readable medium of claim 8 , wherein sorting the biometric features comprises:

performing a weighted summation on at least two frequencies for a first biometric feature of the biometric features to obtain a frequency value; and

sorting the biometric features based on the weighted summation.

11. The non-transitory, computer-readable medium of claim 8 , wherein the operations comprise:

comparing a given biometric feature of the user with a given biometric feature in the identified biometric feature database;

updating, as an updated frequency, a frequency of the given biometric feature in the identified biometric feature database when a match is determined based on comparing the given biometric feature of the user with the given biometric feature in the identified biometric feature database; and

rearranging the biometric features in the identified biometric feature database based on the updated frequency.

12. The non-transitory, computer-readable medium of claim 8 , wherein the biometric features comprise a facial feature.

13. The non-transitory, computer-readable medium of claim 12 , wherein the operations comprise:

obtaining, as an obtained user facial feature, a user facial feature of the user;

comparing the obtained user facial feature with the biometric features in the identified biometric feature database; and

when a matched facial feature is obtained, performing a payment by using a payment account corresponding to the facial feature.

14. The non-transitory, computer-readable medium of claim 13 , wherein the obtained user facial feature of the user is compared with the biometric features in the identified biometric feature database based on feature ranks, wherein feature ranks are obtained after the biometric features in the identified biometric feature database are sorted.

15. A computer-implemented system, comprising:

one or more computers; and

one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations, comprising:

determining, for each type of biometric identification of a plurality of different types of biometric identification, a frequency with which a type of biometric identification is successful in matching a corresponding biometric feature of a user that is associated with the type of biometric identification;

sorting, in descending order and as sorted biometric features, corresponding biometric features according to the frequency with which the plurality of different types of biometric identification that are associated with the corresponding biometric features are successful in matching corresponding biometric features feature of the user, wherein the corresponding biometric features correspond to elements for biometric identification of one or more users;

prioritizing access in a biometric feature database and to a particular biometric feature having a highest value of frequency of successful matching of the particular biometric feature by storing, in descending order and in the biometric feature database corresponding to a first merchant that is accessed when performing the different types of biometric identification, the sorted biometric features, wherein biometric features that are associated with types of biometric identification that have a higher frequency of successful matching are stored, with respect to descending order, at a higher value earlier positions in the biometric feature database when compared to biometric features that are associated with types of biometric information that have a lower frequency of successful matching;

obtaining a verification code corresponding to the first merchant that is allocated to the user, wherein different verification codes are allocated to different users;

generating a hash value corresponding to the verification code by performing a hash function calculation on the verification code, wherein different biometric features are stored in different biometric feature databases based on a corresponding hash value;

identifying, as an identified biometric feature database, the biometric feature database corresponding to the first merchant based on the hash value corresponding to the verification code; and

performing biometric identification based on the identified biometric feature database and the sorted biometric features.

16. The computer-implemented system of claim 15 , wherein the frequency is a mathematical function of at least one of a number of times that a first biometric feature of the biometric features has been requested or a most recent usage time that the first biometric feature was matched.

17. The computer-implemented system of claim 15 , wherein sorting the biometric features comprises:

performing a weighted summation on at least two frequencies for a first biometric feature of the biometric features to obtain a frequency value; and

sorting the biometric features based on the weighted summation.

18. The computer-implemented system of claim 15 , wherein the operations comprise:

comparing a given biometric feature of the user with a given biometric feature in the identified biometric feature database;

updating, as an updated frequency, a frequency of the given biometric feature in the identified biometric feature database when a match is determined based on comparing the given biometric feature of the user with the given biometric feature in the identified biometric feature database; and

rearranging the biometric features in the identified biometric feature database based on the updated frequency.

19. The computer-implemented system of claim 15 , wherein the biometric features comprise a facial feature.

20. The computer-implemented system of claim 19 , wherein the operations comprise:

obtaining, as an obtained user facial feature, a user facial feature of the user;

comparing the obtained user facial feature with the biometric features in the identified biometric feature database; and

when a matched facial feature is obtained, performing a payment by using a payment account corresponding to the facial feature.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 10, 2020
From: ADVANTAGEOUS NEW TECHNOLOGIES CO., LTD.
To: ADVANCED NEW TECHNOLOGIES CO., LTD.
Reel/Frame 053754/0625 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 31, 2020
From: ALIBABA GROUP HOLDING LIMITED
To: ADVANTAGEOUS NEW TECHNOLOGIES CO., LTD.
Reel/Frame 053743/0464 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 22, 2020
From: ZHAI, FEN; GU, CHUNLEI; LU, LEI; LIU, YANGHUI
To: ALIBABA GROUP HOLDING LIMITED
Reel/Frame 051586/0217 →