CN111950364A - System and method for identifying face of tens of millions of base libraries in different libraries - Google Patents
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Abstract
The invention discloses a system and a method for identifying faces of ten-million level base databases in different databases, wherein the method comprises the following steps: receiving a face picture acquired by image acquisition equipment, and acquiring information of the image acquisition equipment, an organization mechanism where the image acquisition equipment is located and an area where the image acquisition equipment belongs; determining a database corresponding to the home region of the image acquisition equipment; identifying the face picture in the frequent customer base, if not, identifying in a corresponding city base, and if not, identifying in a silent base; if the human face picture is identified in the frequent flyer library, the city library or the silence library, acquiring natural human information corresponding to the human face picture; if the silence database is not identified, the client corresponding to the face picture is judged to be a stranger, and the identification information corresponding to the face picture is sent to a stranger base database. By the technical scheme, the development cost and the hardware cost are reduced while the function operation of the ten-million-level database is ensured, and the horizontal expansion newly-added capability of the face database is improved.
Description
Technical Field
The invention relates to the technical field of databases, in particular to a database-based face recognition system and a database-based face recognition method for a million-level base.
Background
In the falling process of products in the intelligent business hall, the face recognition technology based on AI has the database building requirement of a face database, the data of the face database is the most important data, and the existing products rarely have the face database with the size of more than 10W. When the human face base reaches more than 10W grade, the problems of low identification accuracy and insufficient performance exist, so that the database partitioning strategy becomes a special strategy to solve.
Disclosure of Invention
Aiming at the problems, the invention provides a database dividing face recognition system and a database dividing face recognition method for a million-level database, which are characterized in that a database dividing strategy of distributed processing is adopted, a face recognition process is combined with properties of a hall of a business hall image acquisition device to perform data routing, and million-level data are distributed in a plurality of hundred thousand-level or million-level data bases to be processed, so that the development cost and the hardware cost are reduced while the function operation of the million-level data bases is ensured, the development efficiency is improved, the horizontal expansion newly-added capability of the face data bases is improved, and the high availability of a face recognition system is improved.
In order to achieve the above object, the present invention provides a database-based face recognition system for ten million level base databases, comprising: the system comprises an image acquisition module, a data analysis module, a mature client library module, a city library module, a silence library module, a stranger library module and an image identification module; the image acquisition module is used for acquiring a face picture; the data analysis module is used for acquiring the equipment information of the image acquisition module, the organization mechanism where the image acquisition module is located and the region to which the image acquisition module belongs, and determining a database corresponding to the region to which the image acquisition module belongs; the mature client library module, the city library module, the silence library module and the stranger library module are respectively used for storing client face pictures and visiting record information in a warehouse-by-warehouse manner; the image recognition module is used for carrying out step-by-step recognition and comparison on the collected face pictures and the face pictures of the clients in the mature client library module, the city library module and the silence library module, acquiring natural person information corresponding to the face pictures when recognition is successful, judging that the client corresponding to the face pictures is a stranger when recognition is unsuccessful, and sending recognition information to a stranger base library.
In the above technical solution, preferably, the database-based face recognition system of the million-level base further includes a data updating module and a data pushing module, after obtaining the natural person information corresponding to the face picture, the data updating module updates and queries a natural person table, obtains the last time of the natural person, and judges whether the face picture is collected newly according to a preset logic and a time difference between two collected face pictures; if the face picture is collected as a new visit, generating a new visit record, and matching the collected face picture with the visit record and then warehousing; if the face picture is not a new visit, inquiring a visit record, matching the collected face picture with the latest visit record and then warehousing; and updating the natural person list according to the put-in face pictures, identifying the natural person list and pushing the natural person list to an appointed party through the data pushing module.
In the above technical solution, preferably, the database-based face recognition system of ten-million levels of base databases further includes a data correction module, where the data correction module obtains information of the record table or the natural people table, analyzes the recognized face picture in combination with a big data module, queries whether the face picture exists in the corresponding base database, if so, obtains an attribution area corresponding to the base database, determines whether the base databases are matched, and if not, performs base database data migration; and if the data do not exist, inquiring a stranger bottom library, and transferring the data in the stranger bottom library to a local market library of a corresponding attribution area.
In the above technical solution, preferably, the mature client database module is a client database whose number of times of faces collected in a preset time reaches a preset number, the silent client database module is a client database whose number of faces are not collected in a preset time, and the city database module is a client database corresponding to an image collection device home region where faces are collected.
The invention also provides a sub-library face recognition method of the million level base, which is applied to the sub-library face recognition system of the million level base in any one of the technical schemes and comprises the following steps: receiving a face picture acquired by image acquisition equipment, and acquiring information of the image acquisition equipment, an organization mechanism where the image acquisition equipment is located and an area where the image acquisition equipment is located; determining a database corresponding to the attribution area of the image acquisition equipment according to the information of the image acquisition equipment; identifying the face picture in a frequent customer base, if the frequent customer base is not identified, identifying the face picture in a city base corresponding to the image acquisition equipment, and if the frequent customer base is not identified, identifying the face picture in a silence base which is not acquired by the image acquisition equipment within preset time; if the human face picture is identified in the frequent customer library, the city library or the silence library, acquiring natural human information corresponding to the human face picture; if the silence library is not identified yet, judging that the client corresponding to the face picture is a stranger, and sending identification information corresponding to the face picture to a stranger base library.
In the above technical solution, preferably, the method for identifying a face in a ten-million level base by sub-base further includes: after the natural person information corresponding to the face picture is obtained, updating and inquiring a natural person table, obtaining the time of the natural person acquired last time, and judging whether the face picture acquisition is a new visit according to preset logic and the time difference of the two acquired face pictures; if the face picture is collected as a new visit, generating a new visit record, and matching the collected face picture with the visit record and then warehousing; if the face picture is not a new visit, inquiring a visit record, matching the collected face picture with the latest visit record and then warehousing; and updating the natural person list according to the put-in face picture, identifying the natural person list and pushing the natural person list to an appointed party.
In the foregoing technical solution, preferably, the determining that the client corresponding to the face picture is a stranger and sending the identification information corresponding to the face picture to a stranger base library specifically includes: after judging that the client corresponding to the face picture is a stranger, recognizing the face picture again, if the recognition is successful, warehousing the face picture into a stranger table, and if the recognition is not successful, warehousing the face picture into a stranger base library and then warehousing the face picture into the stranger table; and updating the newly-stored stranger information to a record table according to the stranger table, identifying the record table and pushing the record table to an appointed party.
In the above technical solution, preferably, the method for identifying a face in a ten-million level base by sub-base further includes: acquiring information of the record list or the natural person list, and analyzing the identified face picture; inquiring whether the face picture exists in a corresponding database, if so, acquiring an attribution area corresponding to the database, judging whether the database is matched, and if not, performing database data migration; and if the face picture does not exist in the corresponding database, inquiring a stranger database, and transferring the data in the stranger database to a city database of the corresponding attribution area.
In the above technical solution, preferably, the big data module is combined to analyze and query the recognized face picture, so as to migrate the database to realize data correction.
In the above technical solution, preferably, the customer data of the face collected in the silent library is migrated to a local market library in the area of the image collecting device, the customer data of which the number of times of the face collected in the local market library in a preset time reaches a preset number is migrated to the frequent customer library, and the customer data of which the number of times of the face collected in the local market library in the preset time does not reach the preset number is migrated to the silent library.
Compared with the prior art, the invention has the beneficial effects that: by means of a distributed processing database dividing strategy, data routing is carried out on the face recognition process in combination with properties of a hall store of a business hall image acquisition device, and ten-million-level data are distributed in a plurality of hundred-thousand-level or million-level data bases for processing, so that the development cost and hardware cost are reduced while the function operation of the ten-million-level data bases is ensured, the development efficiency is improved, the horizontal expansion newly-added capability of the face data bases is improved, and the high availability of the face recognition system is improved.
Drawings
Fig. 1 is a block diagram schematically illustrating a structure of a database-based face recognition system of a million-level base according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a method for identifying faces of ten-million base sub-bases according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a data correction method according to an embodiment of the present invention.
In the drawings, the correspondence between each component and the reference numeral is:
11. the system comprises an image acquisition module, 12 a data analysis module, 13 a mature library module, 14 a city library module, 15 a silence library module, 16 a stranger library module, 17 an image recognition module, 18 a data updating module, 19 a data pushing module and 20 a data correction module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The invention is described in further detail below with reference to the attached drawing figures:
as shown in fig. 1, the present invention provides a face recognition system for tens of millions of bases, which includes: the system comprises an image acquisition module 11, a data analysis module 12, a mature client library module 13, a city library module 14, a silence library module 15, a stranger library module 16 and an image recognition module 17; the image acquisition module 11 is used for acquiring a face picture; the data analysis module 12 is configured to obtain the device information of the image acquisition module 11, the organization and the region to which the device information belongs, and determine a database corresponding to the region to which the device information belongs; the mature client library module 13, the city library module 14, the silence library module 15 and the stranger library module 16 are respectively used for storing client face pictures and visiting record information in a warehouse-by-warehouse manner; the image recognition module 17 is used for carrying out step-by-step recognition comparison on the collected face picture and the face pictures of the clients in the mature client library module 13, the city library module 14 and the silence library module 15, acquiring natural person information corresponding to the face picture when recognition is successful, judging that the client corresponding to the face picture is a stranger when recognition is unsuccessful, and sending the recognition information to a stranger base library.
In the embodiment, through a distributed processing database partitioning strategy, a face recognition process is combined with properties of a hall of a business hall image acquisition device to perform data routing, and ten-million-level data is distributed in a plurality of hundred-thousand-level or million-level data bases to be processed, so that the development cost and the hardware cost are reduced while the function operation of the ten-million-level data bases is ensured, the development efficiency is improved, the horizontal expansion newly-added capability of the face data bases is improved, and the high availability of a face recognition system is improved.
Preferably, the mature library module 13 is a customer database whose number of faces collected in a preset time reaches a preset number, the silent library module 15 is a customer database whose number of faces is not collected in a preset time, and the city library module 14 is a customer database corresponding to the home area of the image collecting device for collecting faces.
Specifically, in this embodiment, taking the face recognition system of the intelligent business hall as an example, the image acquisition module 11 is an image acquisition device (preferably a camera) in the business hall, and the mature library module 13, the city library module 14, the silence library module 15 and the stranger library module 16 are different databases, and are respectively used for storing a face picture and visiting record information of a visiting client visiting the intelligent business hall. The data analysis module 12 determines a database corresponding to the region of the image acquisition device by analyzing information such as an organization code, the region, a device IP, and a device ID to which the image acquisition device belongs, so as to support a human face database of a larger magnitude by a sub-database strategy of the region to which the image acquisition device belongs.
The image recognition module 17 is configured to compare and recognize the face pictures captured by the image capturing device in the business hall with the databases in different levels, and determine whether each database includes face information matched with the face picture. The sequence of face picture comparison and recognition is carried out from a database of a high-frequency visiting business hall to a database of a low-frequency visiting business hall, all databases are classified according to visiting frequency and areas, the database partitioning strategy and the face recognition process are designed in a nested mode, and functions of a database of ten-million magnitude or higher magnitude are achieved in a distributed mode through a small database of one hundred-million magnitude or million magnitude.
In the above embodiment, preferably, the database-based face recognition system of the million-level base further includes a data updating module 18 and a data pushing module 19, after obtaining the natural person information corresponding to the face picture, the data updating module 18 updates and queries a natural person table, obtains the time of the natural person acquired last time, and judges whether the face picture acquisition is a new visit according to a preset logic and a time difference between two acquired face pictures; if the face picture is collected as a new visit, generating a new visit record, and matching the collected face picture with the visit record and then warehousing; if the face picture is not a new visit, inquiring a visit record, matching the collected face picture with the latest visit record and then warehousing; and updating the natural person list according to the face picture in storage, identifying the natural person list and pushing the natural person list to the appointed party through the data pushing module 19.
Through the comparison and recognition among the image recognition module 17, the mature client library module 13, the city database module 14 and the silence database module 15, the data updating module 18 updates the visiting records and the strange visitor tables in the face recognition system according to the comparison and recognition results, stores corresponding face pictures into corresponding data bases, and pushes the face pictures and table information to a preset appointed party, such as a data correction module, through the data pushing module 19.
In the above embodiment, preferably, the database-based face recognition system of ten-million levels of base databases further includes a data correction module 20, where the data correction module 20 obtains information of a record table or a natural person table, analyzes an identified face picture in combination with a big data module, and queries whether the face picture exists in the corresponding base database, if so, obtains an attribution area corresponding to the base database, determines whether the base databases are matched, and if not, performs base database data migration; and if the data do not exist, inquiring the stranger bottom library, and transferring the data in the stranger bottom library to a local market library of the corresponding attribution area.
As shown in fig. 2, the present invention further provides a method for identifying faces of ten-million level bases, which is applied to the system for identifying faces of ten-million level bases in any of the above embodiments, and includes: receiving a face picture acquired by image acquisition equipment, and acquiring information of the image acquisition equipment, an organization mechanism where the image acquisition equipment is located and an area where the image acquisition equipment belongs; determining a database corresponding to the image acquisition equipment home region according to the information of the image acquisition equipment; identifying the face picture in the frequent customer base, if not, identifying the face picture in a local market base corresponding to the image acquisition equipment, and if not, identifying the face picture in a silent base which is not acquired by the image acquisition equipment within preset time; if the human face picture is identified in the frequent flyer library, the city library or the silence library, acquiring natural human information corresponding to the human face picture; if the silence database is not identified, the client corresponding to the face picture is judged to be a stranger, and the identification information corresponding to the face picture is sent to a stranger base database.
In the embodiment, the face pictures captured and collected by the image collecting device in the business hall are respectively compared with the databases in different levels for identification, and whether the databases contain face information matched with the face pictures or not is judged. The sequence of face picture comparison and recognition is carried out from a database of a high-frequency visiting business hall to a database of a low-frequency visiting business hall, all databases are classified according to visiting frequency and areas, the database partitioning strategy and the face recognition process are designed in a nested mode, and functions of databases of ten million magnitude or higher magnitude are achieved in a distributed mode through a small database of hundred thousand magnitude or million magnitude.
In the above embodiment, preferably, the method for identifying faces in ten-million levels of base libraries further includes: after obtaining the natural person information corresponding to the face picture, updating and inquiring a natural person table, obtaining the time of the natural person acquired last time, and judging whether the face picture acquisition is a new visit or not according to preset logic and the time difference of the two acquired face pictures; if the face picture is collected as a new visit, generating a new visit record, and matching the collected face picture with the visit record and then warehousing; if the face picture is not a new visit, inquiring a visit record, matching the collected face picture with the latest visit record and then warehousing; and updating the natural person list according to the put-in face picture, identifying the natural person list and pushing the natural person list to an appointed party. Through the comparison and recognition among the face picture, the mature client library module 13, the city library module 14 and the silence library module 15, the visiting record and the strange visitor list in the face recognition system are updated according to the comparison and recognition result, the corresponding face picture is put into a corresponding data base, and the face picture and the list information are pushed to a preset appointed party.
In the above embodiment, preferably, the determining that the client corresponding to the face picture is a stranger and sending the identification information corresponding to the face picture to the stranger database specifically includes: after judging that the client corresponding to the face picture is a stranger, recognizing the face picture again, if the recognition is successful, warehousing the face picture into a stranger table, and if the recognition is not successful, warehousing the face picture into a stranger base library and then warehousing the face picture into the stranger table; and updating the newly-stored stranger information to a record table according to the stranger table, identifying the record table and pushing the record table to an appointed party.
As shown in fig. 3, in the foregoing embodiment, preferably, the method for identifying faces in ten-million base sub-bases further includes: acquiring information of a record table or a natural person table, and analyzing the identified face picture by combining a big data module; querying whether the face picture exists in a corresponding database by combining a big data module, if so, acquiring an attribution area corresponding to the database, judging whether the database is matched, and if not, migrating the database data; and if the face picture does not exist in the corresponding database, inquiring a stranger database, and transferring the data in the stranger database to a city database of the corresponding attribution area.
In the above embodiment, preferably, in the data correction process, the customer data of the faces collected in the silence repository is migrated to a local store in the image collection device area, the customer data of which the number of times of the faces collected in the local store within a preset time reaches a preset number is migrated to a frequent customer store, and the customer data of which the number of times of the faces collected in the local store within the preset time does not reach the preset number is migrated to the silence repository.
And the data in the data base is migrated through the background, and each data base is classified according to the visiting frequency and the belonging area, so that the data is migrated to the data base corresponding to the visiting frequency in the migration process according to the updating of the visiting frequency information in the record table or the natural person table, and the data correction is realized, so that the new visiting client can be identified more quickly and optimally.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A face recognition system for tens of millions of base libraries is characterized by comprising: the system comprises an image acquisition module, a data analysis module, a mature client library module, a city library module, a silence library module, a stranger library module and an image identification module;
the image acquisition module is used for acquiring a face picture;
the data analysis module is used for acquiring the equipment information of the image acquisition module, the organization mechanism where the image acquisition module is located and the region to which the image acquisition module belongs, and determining a database corresponding to the region to which the image acquisition module belongs;
the mature client library module, the city library module, the silence library module and the stranger library module are respectively used for storing client face pictures and visiting record information in a warehouse-by-warehouse manner;
the image recognition module is used for carrying out step-by-step recognition and comparison on the collected face pictures and the face pictures of the clients in the mature client library module, the city library module and the silence library module, acquiring natural person information corresponding to the face pictures when recognition is successful, judging that the client corresponding to the face pictures is a stranger when recognition is unsuccessful, and sending recognition information to a stranger base library.
2. The database-based face recognition system of ten-million levels of basements according to claim 1, further comprising a data updating module and a data pushing module, wherein after the natural person information corresponding to the face picture is obtained, the data updating module updates and queries a natural person table, obtains the last time of the natural person, and judges whether the face picture collection is a new visit according to a preset logic and a time difference between two collected face pictures;
if the face picture is collected as a new visit, generating a new visit record, and matching the collected face picture with the visit record and then warehousing;
if the face picture is not a new visit, inquiring a visit record, matching the collected face picture with the latest visit record and then warehousing;
and updating the natural person list according to the put-in face pictures, identifying the natural person list and pushing the natural person list to an appointed party through the data pushing module.
3. The database-based face recognition system according to claim 1, further comprising a data correction module, wherein the data correction module acquires information of the record table or the natural people table, analyzes the recognized face picture in combination with a big data module, queries whether the face picture exists in the corresponding database, acquires an attribution area corresponding to the database if the face picture exists, determines whether the database is matched, and performs database data migration if the face picture does not match; and if the data do not exist, inquiring a stranger bottom library, and transferring the data in the stranger bottom library to a local market library of a corresponding attribution area.
4. The database-based face recognition system of ten-million level bases according to claim 1, wherein the mature client database module is a client database whose number of face collection times reaches a preset number within a preset time, the silent client database module is a client database whose face is not collected within a preset time, and the city database module is a client database corresponding to the home region of the image collection device for collecting the face.
5. A database-based face recognition method of a million-level base is applied to the database-based face recognition system of the million-level base according to any one of claims 1 to 4, and is characterized by comprising the following steps:
receiving a face picture acquired by image acquisition equipment, and acquiring information of the image acquisition equipment, an organization mechanism where the image acquisition equipment is located and an area where the image acquisition equipment is located;
determining a database corresponding to the attribution area of the image acquisition equipment according to the information of the image acquisition equipment;
identifying the face picture in a frequent customer base, if the frequent customer base is not identified, identifying the face picture in a city base corresponding to the image acquisition equipment, and if the frequent customer base is not identified, identifying the face picture in a silence base which is not acquired by the image acquisition equipment within preset time;
if the human face picture is identified in the frequent customer library, the city library or the silence library, acquiring natural human information corresponding to the human face picture;
if the silence library is not identified yet, judging that the client corresponding to the face picture is a stranger, and sending identification information corresponding to the face picture to a stranger base library.
6. The method for identifying the face of the ten-million level base according to claim 5, further comprising: after the natural person information corresponding to the face picture is obtained, updating and inquiring a natural person table, obtaining the time of the natural person acquired last time, and judging whether the face picture acquisition is a new visit according to preset logic and the time difference of the two acquired face pictures;
if the face picture is collected as a new visit, generating a new visit record, and matching the collected face picture with the visit record and then warehousing;
if the face picture is not a new visit, inquiring a visit record, matching the collected face picture with the latest visit record and then warehousing;
and updating the natural person list according to the put-in face picture, identifying the natural person list and pushing the natural person list to an appointed party.
7. The database-based face recognition method of the million-level base, according to claim 6, wherein the judging that the client corresponding to the face picture is a stranger and sending the recognition information corresponding to the face picture to a stranger base specifically comprises:
after judging that the client corresponding to the face picture is a stranger, recognizing the face picture again, if the recognition is successful, warehousing the face picture into a stranger table, and if the recognition is not successful, warehousing the face picture into a stranger base library and then warehousing the face picture into the stranger table;
and updating the newly-stored stranger information to a record table according to the stranger table, identifying the record table and pushing the record table to an appointed party.
8. The method for identifying the face of the ten-million level base according to claim 7, further comprising:
acquiring information of the record list or the natural person list, and analyzing the identified face picture;
inquiring whether the face picture exists in a corresponding database, if so, acquiring an attribution area corresponding to the database, judging whether the database is matched, and if not, performing database data migration;
and if the face picture does not exist in the corresponding database, inquiring a stranger database, and transferring the data in the stranger database to a city database of the corresponding attribution area.
9. The method for identifying the face of each of ten million levels of bases according to claim 8, wherein a big data module is combined to analyze and query the identified face picture so as to migrate the database base to realize data correction.
10. The database-based face recognition method according to claim 9, wherein the customer data of the faces collected in the silence database is migrated to a city database in the area of the image collection device, the customer data of the number of collected faces in the city database reaching a preset number within a preset time is migrated to the frequent customer database, and the customer data of the number of collected faces in the city database not reaching the preset number within the preset time is migrated to the silence database.
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| CN202010647085.8A CN111950364B (en) | 2020-07-07 | 2020-07-07 | System and method for identifying library-separating face of tens of millions of libraries |
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| CN202010647085.8A CN111950364B (en) | 2020-07-07 | 2020-07-07 | System and method for identifying library-separating face of tens of millions of libraries |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113190707A (en) * | 2021-05-24 | 2021-07-30 | 浙江大华技术股份有限公司 | Face library management system, method and device, storage equipment and storage medium |
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