CN109887114A - Face batch identification attendance system and method - Google Patents
Face batch identification attendance system and method Download PDFInfo
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- CN109887114A CN109887114A CN201811608358.7A CN201811608358A CN109887114A CN 109887114 A CN109887114 A CN 109887114A CN 201811608358 A CN201811608358 A CN 201811608358A CN 109887114 A CN109887114 A CN 109887114A
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Abstract
The invention discloses face batch identification attendance system and methods, people's image in the panoramic image file of upload detected including data acquisition device, model generation module, data processing module, data disaply moudle, data memory module, report generation module using the object detection method based on deep learning, positioned and, the step of every facial image being syncopated as in the panoramic image file, comprising: carry out the facial image detected in the panoramic image file to cut figure, coding and filing.
Description
Technical field
The present invention relates to field of face identification, specially face batch identification attendance system and method.
Background technique
Face recognition technology carries out identification to the character facial physical features in picture or video, thus to certification
Rear face carries out subsequent sequence of operations, and main available large scene includes security protection, safety check, and traffic administration etc. is small-sized
Scene includes domestic safety monitoring, company's attendance etc., is substantially all currently used as the face recognition technology of attendance and is absorbed in design
One attendance recorder device, this device include a mininet camera, the display screen of a small-sized face size, it is possible to
It further include a fingerprint identification device.After the technology, employee, which enters company, must be lined up by this attendance recorder, if public
Department's scale is bigger, and headcount is more, this, which will lead to some problems, occurs: employee is lined up in the commuter time passes through attendance
Many quantity attendance recorders, cost are relatively high in order to which attendance needs to buy for machine, attendance overlong time, attendance low efficiency, and company.
Summary of the invention
To achieve the above object, the invention provides the following technical scheme: face batch identification attendance checking system, comprising:
Data acquisition module, while acquiring the face image data of at least two attendance objects；
Model generation module obtains face prediction model, root by face recognition algorithms according to the face image data
The mark ID of corresponding attendance object is matched according to the face prediction model, obtains face recognition result, and pass through the mark
Know the image set that the image data of the collected face is stored in corresponding attendance object by ID respectively according to predetermined format
In；
Face recognition result is pushed into message queue by data processing module, and passes through the message queue batch
The face recognition result is handled, and after receiving the application for subscribing to the message queue, the face recognition result is sent
To data disaply moudle, while in the database by face recognition result record；
Data disaply moudle receives the face recognition result that data processing module is sent, and by the face recognition result
It is output to display terminal.
Further, further include data memory module, face recognition result time segment is stored in special distribution
On data memory node.
Data disaply moudle receives the face recognition result that data processing module is sent, and by the face recognition result
It is output to display terminal.
Further, further include data memory module, face recognition result time segment is stored in special distribution
On data memory node.
Further, further include report generation module, the various reports that attendance needs are generated according to face recognition result.
Further, the data acquisition module includes web terminal, uploads personal face image data by web terminal
Collect the image data of the face.
Further, each attendance object of the data-base recording daily for the first time by time of human face identification work-attendance checking with
And the time that last time passes through human face identification work-attendance checking.
Further, pass through the face recognition result in the database purchase message queue, the letter of multiple attendance objects
Breath is stored in a database.
Further, the report generation module provides various reports required for attendance, including attendance object work number, surname
Name, commuter time and overtime.
The present invention also provides a kind of face batch identification Work attendance methods, include the following steps:
Step S1: while acquiring the face image data of at least two attendance objects；
Step S2: face prediction model is obtained by face recognition algorithms according to the face image data, according to described
Face prediction model matches the mark ID of corresponding attendance object, obtains face recognition result, and will by the mark ID
The image data of the collected face is stored in respectively in the image set of corresponding attendance object according to predetermined format；
Step S3: face recognition result is pushed into message queue, and passes through the message queue batch processing institute
Face recognition result is stated, and after receiving the application for subscribing to the message queue, the face recognition result is sent to data
Display module, while in the database by face recognition result record；
Step S4: the face recognition result that data processing module is sent is received, and the face recognition result is output to
Display terminal.
Further, face recognition result time segment is stored on special Distributed Storage node.
Further, step S1 is specifically included: being uploaded personal face image data by web terminal and is collected the people
The image data of face, and/or the image data of the face is obtained by the overlay area automatic collection of camera.
Further, each attendance object of the data-base recording daily for the first time by time of human face identification work-attendance checking with
And the time that last time passes through human face identification work-attendance checking.
Further, the various reports that attendance needs are generated according to face recognition result.
Further, by the database purchase message queue as a result, more people's information are stored in a database
In.
By the face recognition result in the database purchase message queue, the information of multiple attendance objects is stored in one
In a database.
Compared with prior art, the beneficial effects of the present invention are:
The same equipment can identify multiple people simultaneously in this system, can detect the face of numerous employees, nothing simultaneously
Must employee come off duty to queue to before attendance recorder and carry out brush face operation, improve attendance efficiency, reduce attendance cost.
Detailed description of the invention:
Fig. 1 is the noninductive identification attendance checking system figure of Europa face batch proposed by the present invention；
Fig. 2 is model generation module mind map of the present invention；
Fig. 3 is the noninductive identification control figure of face batch of the present invention；
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
Fig. 1-3 is please referred to, the embodiment of the present invention provides a kind of face batch identification attendance checking system, comprising: data acquisition module
Block, while acquiring the face image data of at least two attendance objects；
Model generation module obtains face prediction model, root by face recognition algorithms according to the face image data
The mark ID of corresponding attendance object is matched according to the face prediction model, obtains face recognition result, and pass through the mark
Know the image set that the image data of the collected face is stored in corresponding attendance object by ID respectively according to predetermined format
In；
Face recognition result is pushed into message queue by data processing module, and passes through the message queue batch
The face recognition result is handled, and after receiving the application for subscribing to the message queue, the face recognition result is sent
To data disaply moudle, while in the database by face recognition result record；
Data disaply moudle receives the face recognition result that data processing module is sent, and by the face recognition result
It is output to display terminal.
Preferably, system further includes data memory module, and face recognition result time segment is stored in special distribution
On formula data memory node.
Data disaply moudle receives the face recognition result that data processing module is sent, and by the face recognition result
It is output to display terminal.
Preferably, system further includes data memory module, and face recognition result time segment is stored in special distribution
On formula data memory node.
Preferably, system further includes report generation module, generates the various reports that attendance needs according to face recognition result.
Preferably, the data acquisition module includes web terminal, uploads personal face image data by web terminal and adopts
Collection obtains the image data of the face.
Preferably, each attendance object of the data-base recording daily for the first time by time of human face identification work-attendance checking and
The time that last time passes through human face identification work-attendance checking.
Preferably, pass through the face recognition result in the database purchase message queue, the information of multiple attendance objects
It is stored in a database.
Preferably, the report generation module provides various reports required for attendance, including attendance object work number, surname
Name, commuter time and overtime.
Above-described embodiment specific implementation operation can be as described below:
Part of data acquisition is divided into two methods, and one is employees to upload personal face image data by web terminal, another
Kind is that employee passes through camera overlay area automatic collection employee face or humanoid image data.The face's number collected
According to by positioning, the training image calibrated, be uniformly cut to 96x96 size, this atlas is then respectively put into each employee's
Training set is used as under id.
Model generates can be by neural network model by back propagation and the optimization loss of stochastic gradient descent method
Function Triplet Loss, obtains the eigenmatrix of 128 dimension of face, obtains finally by SVM support vector cassification algorithm
Final face prediction model.
Face recognition result is pushed into message queue, and terminal subscribes to the message queue, receives prediction result, will be tied
Fruit is shown on video, while data persistence being recorded in Mysql database.
Face attendance checking system obtains data processing module subscription by access rtmp streaming media video server at the same time
To multiple face recognition results be output in video flowing, multiple face attendance situations in video can be watched in real time in this way
Recognition of face monitor video time segment is stored on special Distributed Storage node.
Wherein, in the data acquisition module, camera can regard DS-2DC2204IW-DE3/W mini using Haikang prestige
PTZ camera ball machine (without being limited thereto, to be merely illustrative herein), 2,000,000 pixels, infrared 30m detection range, PoE power supply, 4
Zoom Lens.It can control the upper and lower, left and right rotation process of camera using Haikang Wei Shi camera official SDK, it can be with
Picture direction is controlled, picture size can control by zoom.Video service will be directly integrated into the code of camera operation
In device, access server can movement to camera or posture be adjusted.When shooting, pass through what is pre-seted
EasyDarwin increases income video server to camera solution agreement (RTSP), decodes (H264), can steadily by video flowing with
The frame per second of 40 milliseconds or so of delay, 25fps is transferred to algoritic module.Multiple cameras pass through cable LAN or wireless office
Domain net is connected to video server unified management, and video server can manage multiple cameras, and sub-screen shows each camera shooting
The image of head.
Wherein, in the step S2, can be existed using the model with face ID in predicted pictures or video flowing, accuracy rate
Reach 99.63% in LFW data set, predetermined speed can reach 100 milliseconds of ranks, be able to satisfy the recognition of face of 80,000 people or so.
Wherein, in the step S3, using this message queue can be processed in batches recognition of face as a result, a terminal can
It is processed in batches multiple face informations.In addition, MySql data-base recording is analyzed enters company for the first time in employee 24 hours one day
Time and last time appear in the time on company doorway to judge attendance, at second day 0 from record new one day data.
Further, in the step S4, video server to video flowing solution agreement (RTSP, RTMP), decoding (H264,
H265), it can stablize and show video glibly.
Wherein, in the step S5, using in MySql database purchase message queue as a result, more employee informations store
In a database.
Wherein, the report generation module provides various reports required for attendance, including employee ID, employee name, member
Work work hours, employee's quitting time, employee's overtime on ordinary days, employee's overtime at weekend.System manager can specify
Work hours section, quitting time section, overtime section also can specify rule generates which employee of some department in certain time
Attendance situation.
The present invention also provides the noninductive identification Work attendance methods of Europa face batch, including record employee information and employee to beat
Card attendance record, and the employee information and record of checking card are uploaded to attendance data library；
According to the data for record of checking card, the panoramic image file at automatic collection attendance scene, and by the panorama of acquisition
Image file is uploaded to the attendance data library, carries out people to the panoramic image file being uploaded in the attendance data library
Face identifying processing, every facial image being syncopated as in the panoramic image file, to the every facial image and institute being syncopated as
It states the employee information recorded in attendance data library to be matched, and matching result is exported into the attendance data library,
Establish attendance relationship.
Wherein, using the object detection method based on deep learning to people's image in the panoramic image file of upload
It detected, positioned also, the step of every facial image being syncopated as in the panoramic image file, comprising: by institute
The facial image detected in panoramic image file is stated to carry out cutting figure, coding and filing.
The embodiment of the present invention also provides a kind of face batch identification Work attendance method, includes the following steps:
Step S1: while acquiring the face image data of at least two attendance objects；
Step S2: face prediction model is obtained by face recognition algorithms according to the face image data, according to described
Face prediction model matches the mark ID of corresponding attendance object, obtains face recognition result, and will by the mark ID
The image data of the collected face is stored in respectively in the image set of corresponding attendance object according to predetermined format；
Step S3: face recognition result is pushed into message queue, and passes through the message queue batch processing institute
Face recognition result is stated, and after receiving the application for subscribing to the message queue, the face recognition result is sent to data
Display module, while in the database by face recognition result record；
Step S4: the face recognition result that data processing module is sent is received, and the face recognition result is output to
Display terminal.
Preferably, face recognition result time segment is stored on special Distributed Storage node.
Preferably, step S1 is specifically included: being uploaded personal face image data by web terminal and is collected the face
Image data, and/or the image data of the face is obtained by the overlay area automatic collection of camera.
Preferably, each attendance object of the data-base recording daily for the first time by time of human face identification work-attendance checking and
The time that last time passes through human face identification work-attendance checking.
Preferably, the various reports that attendance needs are generated according to face recognition result.
Preferably, by the database purchase message queue as a result, more people's information are stored in a database.
By the face recognition result in the database purchase message queue, the information of multiple attendance objects is stored in one
In a database.
In above-mentioned all example schemes, a variety of checking-in states can be carried out certainly using batch human face identification work-attendance checking system
Defining operation, customized setting work hours section, quitting time section, overtime section, to meet a variety of attendance demands.
In above-described embodiment scheme, camera can be used the existing PTZ security protection camera of company and be deployed in appropriate position
It sets connection finite element network or batch attendance checking function can be realized in wireless network, without using attendance recorder not only brush face but also brush finger
Line further decreases attendance cost, improves attendance efficiency.
In above-described embodiment scheme, attendance checking system can be unified by algorithm micro services by the way of Docker micro services
Kubernate is transferred to dispatch, a frame data can provide calculating by polyalgorithm micro services, then prediction result is aggregated into this
Above the image of frame, this is done so that the batch identifications of face to be possibly realized, by the speed of greatly optimization monitoring real-time video.
One concrete application of the present embodiment are as follows: check card attendance record including record employee information and employee, and will be described
Employee information and record of checking card are uploaded to attendance data library；According to the data for record of checking card, the panorama at automatic collection attendance scene
Image file, and the panoramic image file of acquisition is uploaded to the attendance data library, to being uploaded to the attendance data
The panoramic image file in library carries out recognition of face processing, every face figure being syncopated as in the panoramic image file
Picture matches the employee information recorded in every facial image being syncopated as and the attendance data library, and general
It exports with result into the attendance data library, establishes attendance relationship, using the object detection method based on deep learning to upper
The people's image in the panoramic image file passed is detected, is positioned also, described is syncopated as in the panoramic image file
Every facial image the step of, the facial image detected in the panoramic image file cut figure, coding
And filing, it is uploaded to of every facial image in the panoramic image file in the attendance data library and employee information
With relationship, also, after establishing the attendance relationship, record is not matched to the employee information of the facial image, and will not at
The matched information of function is issued to corresponding employee, not successfully when matched information, during specifying a complaint, also, the attendance number
Evidence inquiry is provided to the employee during the complaint according to library to service with complaint.
In the description of this specification, the description of reference term " one embodiment ", " example ", " specific example " etc. means
Particular features, structures, materials, or characteristics described in conjunction with this embodiment or example are contained at least one implementation of the invention
In example or example.In the present specification, schematic expression of the above terms may not refer to the same embodiment or example.
Moreover, particular features, structures, materials, or characteristics described can be in any one or more of the embodiments or examples to close
Suitable mode combines.
Present invention disclosed above preferred embodiment is only intended to help to illustrate the present invention.There is no detailed for preferred embodiment
All details are described, are not limited the invention to the specific embodiments described.Obviously, according to the content of this specification,
It can make many modifications and variations.These embodiments are chosen and specifically described to this specification, is in order to better explain the present invention
Principle and practical application, so that skilled artisan be enable to better understand and utilize the present invention.The present invention is only
It is limited by claims and its full scope and equivalent.
Claims (15)
1. face batch identification attendance checking system characterized by comprising
Data acquisition module, while acquiring the face image data of at least two attendance objects；
Model generation module obtains face prediction model by face recognition algorithms according to the face image data, according to institute
The mark ID that face prediction model matches corresponding attendance object is stated, obtains face recognition result, and will by the mark ID
The image data of the collected face is stored in respectively in the image set of corresponding attendance object according to predetermined format；
Face recognition result is pushed into message queue by data processing module, and passes through the message queue batch processing
The face recognition result, and after receiving the application for subscribing to the message queue, the face recognition result is sent to number
According to display module, while in the database by face recognition result record；
Data disaply moudle receives the face recognition result that data processing module is sent, and the face recognition result is exported
To display terminal.
2. face batch identification attendance checking system according to claim 1, which is characterized in that it further include data memory module,
Face recognition result time segment is stored on special Distributed Storage node.
3. face batch identification attendance checking system according to claim 1, which is characterized in that it further include report generation module,
The various reports that attendance needs are generated according to face recognition result.
4. face batch identification attendance checking system according to claim 1, which is characterized in that the data acquisition module includes
Web terminal uploads the image data that personal face image data collects the face by web terminal.
5. face batch identification attendance checking system according to claim 1, which is characterized in that the data acquisition module includes
Camera obtains the image data of the face by the overlay area automatic collection of camera.
6. face batch identification attendance checking system according to claim 1, which is characterized in that the data-base recording is each examined
The time that diligent object passes through human face identification work-attendance checking by the time of human face identification work-attendance checking and last time for the first time daily.
7. face batch identification attendance checking system according to claim 1, which is characterized in that disappeared by the database purchase
The face recognition result in queue is ceased, the information of multiple attendance objects is stored in a database.
8. face batch identification attendance checking system according to claim 3, which is characterized in that the report generation module provides
Various reports required for attendance, including attendance object work number, name, commuter time and overtime.
9. a kind of face batch identification Work attendance method, which comprises the steps of:
Step S1: while acquiring the face image data of at least two attendance objects；
Step S2: face prediction model is obtained by face recognition algorithms according to the face image data, according to the face
Prediction model matches the mark ID of corresponding attendance object, obtains face recognition result, and will acquire by the mark ID
To the face image data be stored in corresponding attendance object respectively according to predetermined format image set in；
Step S3: face recognition result is pushed into message queue, and passes through people described in the message queue batch processing
Face recognition result, and after receiving the application for subscribing to the message queue, the face recognition result is sent to data and is shown
Module, while in the database by face recognition result record；
Step S4: the face recognition result that data processing module is sent is received, and the face recognition result is output to display
Terminal.
10. face batch identification Work attendance method according to claim 9, which is characterized in that further include: by recognition of face knot
Fruit time segment is stored on special Distributed Storage node.
11. face batch identification Work attendance method according to claim 9, which is characterized in that step S1 is specifically included: being passed through
Web terminal uploads the image data that personal face image data collects the face, and/or the area of coverage for passing through camera
Domain automatic collection obtains the image data of the face.
12. face batch identification Work attendance method according to claim 9, which is characterized in that step S1 is specifically included: described
The each attendance object of data-base recording is known by the time of human face identification work-attendance checking and last time by face for the first time daily
The time of other attendance.
13. face batch identification Work attendance method according to claim 9, which is characterized in that further include: according to recognition of face
As a result the various reports that attendance needs are generated.
14. face batch identification Work attendance method according to claim 9, which is characterized in that pass through the database purchase
It is in message queue as a result, more people's information are stored in a database.
15. face batch identification Work attendance method according to claim 9, which is characterized in that pass through the database purchase
Face recognition result in message queue, the information of multiple attendance objects are stored in a database.
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| CN201811608358.7A CN109887114A (en) | 2018-12-27 | 2018-12-27 | Face batch identification attendance system and method |
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