CN105335750A - Client identity identification system and identification method - Google Patents
Client identity identification system and identification method Download PDFInfo
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- CN105335750A CN105335750A CN201410255912.3A CN201410255912A CN105335750A CN 105335750 A CN105335750 A CN 105335750A CN 201410255912 A CN201410255912 A CN 201410255912A CN 105335750 A CN105335750 A CN 105335750A
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Abstract
The invention provides a client identity identification system. The system comprises a server, a display, at least one camera and at least one computer. Each computer comprises a characteristic acquisition module. The server comprises a database, a training module, a registration module, a comparison module and a client determining module. The invention also provides a client identity identification method. The method comprises the steps of acquiring client information, storing the client information to the database, acquiring facial feature information of a person passing the visual field of a pick-up head, successively comparing the facial feature information with facial feature information in the client information of the database, determining whether the person passing the visual field of the pick-up head is stored and recorded in the database, and the like. The system and method have the advantages of rapidly identifying the identity of a guest and accordingly determining whether the guest is a known client.
Description
Technical field
The present invention relates to a kind of client identity recognition system for service location and recognition methods.
Background technology
In the service locations such as market, dining room, coffee shop, hotel, in a lot of situation, need reception personnel can be familiar with consumer status, to provide better service for client.But in practical work, reception personnel can only lean on self memory to remember common client, be difficult to appearance and other data informations of remembeing each client.
Summary of the invention
The invention provides a kind of client identity recognition system, the data such as appearance, identity information effectively solving the corporate client existed in prior art is difficult to many technical matterss such as being remembered.
For realizing above-mentioned goal of the invention, the present invention adopts following technical scheme:
A kind of client identity recognition system, comprising:
One server;
One display;
At least one camera, for taking image through the personnel of this camera view or video; And
At least one computing machine;
Each camera is connected to a computing machine, and each computing machine is connected to described server;
Each computing machine comprises a collection apparatus module, for gathering the face feature information of the described personnel through camera view;
Described server comprises:
One database, for storing customer information, described customer information comprises client identity information and client's face feature information;
One training module, for extracting the face feature information of people and being stored to described database from image;
One Registering modules, for storing described customer information to described database, concurrent customer image of sending is to described training module;
One contrast module, for contrasting the client's face feature information in the face feature information of the described personnel through camera view and described database successively;
One client's determination module, for judging whether the described personnel through camera view have stored record in a database; If so, judge that the described personnel through camera view are as known customer, send the customer information of this known customer to described display; If not, judge that the described personnel through camera view are as unknown client, send result of determination to described display.
Described collection apparatus module comprises:
Image collection module, for obtaining the image of the described personnel through camera view;
Face detection module, for whether there is facial image in detected image, if so, obtains facial image, if not, detects next image;
Facial pretreatment module, for facial image described in pre-service;
Characteristic extracting module, for extracting the facial characteristics of people in described facial image;
Described face detection module is by described facial pretreatment model calling extremely described characteristic extracting module.
Described training module comprises:
Face datection training module, for obtaining facial image;
Facial pretreatment training module, for facial image described in pre-service;
Feature extraction training module, for extracting the feature of described face;
Face datection training module is connected to described feature extraction training module by described facial pretreatment training module.
Described collection apparatus module, described database are connected to described contrast module respectively, and described contrast model calling is to described client's determination module.
Described Registering modules is connected to described database, and described Registering modules is connected to described database by training module.
Described client identity recognition system, also comprises a handheld terminal, is connected to described server by wireless network, for inputting and sending information to server, for showing described customer information and result of determination.
Described handheld terminal comprises touch-screen; Or described handheld terminal comprises keyboard and display screen.
The present invention also provides a kind of client identity recognition methods, comprises the steps:
One display and at least one camera are set;
Gather customer information, described customer information comprises client identity information and client's face feature information;
Gather the face feature information of the described personnel through camera view;
Contrast the face feature information in the face feature information of the described personnel through camera view and the customer information of described database successively;
Judge whether the described personnel through camera view have stored record in a database; If so, judge that the described personnel through camera view are as known customer, send this known customer information to display; If not, judge that the described personnel through camera view are as unknown client, send result of determination to described display.
Described collection customer information, comprises the steps:
Registering modules stores client identity information to database;
Described Registering modules sends customer image to training module;
Described training module extracts client's face feature information and is stored to described database from described customer image.
The face feature information of the described personnel through camera view of described collection, comprises the steps:
Obtain the image of the described personnel through camera view;
Detect in described image and whether there is facial image, if not, detect next image, if so, obtain facial image;
Facial image described in pre-service;
Extract the facial characteristics of people in described facial image.
The invention has the advantages that, guest's identity can be identified fast after guest enters, and then judge whether guest is known customer, if known customer, system can voluntarily in calling data storehouse this client relevant information and be sent on the server of information desk or the handheld terminal of reception personnel; If guest's identity is unknown, judged result can be sent on the server of information desk or the handheld terminal of reception personnel by system, notifies that reception personnel gathers new guest's information simultaneously.
Accompanying drawing explanation
Figure 1 shows that the structural representation of client identity recognition system of the present invention;
Figure 2 shows that the FB(flow block) of client identity recognition methods of the present invention;
Figure 3 shows that in the present invention the FB(flow block) gathering customer information method;
Figure 4 shows that in the present invention the FB(flow block) of the face feature information gathering the described personnel through camera view.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further illustrated.
As shown in Figure 1, the present invention relates to a kind of client identity recognition system, comprising:
A kind of client identity recognition system, is characterized in that, comprising:
One server 1;
One display 2;
At least one camera 3, for taking image through the personnel of this camera view or video; And
At least one computing machine 4;
Each camera 3 is connected to a computing machine 4, and each computing machine 4 is connected to server 1;
Each computing machine 4 comprises a collection apparatus module 41, for gathering the face feature information of the described personnel through camera view; Herein, multiple camera can be distributed in gate inhibition place incessantly, also can be placed on the position that other can monitor client, and such as, in the hall of hotel doorway, receptionist locates, etc.Each camera 3 is all connected with a computing machine 4, the face feature information of each client that the direct acquisition camera of characteristic extracting module 41 can be utilized to monitor.
Collection apparatus module 41 comprises:
Image collection module 411, for obtaining the image of the described personnel through camera view.The video that described camera photographs by image collection module 411 carries out sectional drawing process, forms plurality of pictures.
Face detection module 412, for detecting in described image whether there is facial image, if so, obtains facial image, if not, detects next image.Check processing is carried out to described image, sorter training is carried out to the Harr feature of described image, obtain the boost sorter of a cascade, utilize this sorter to realize Face datection.
Facial pretreatment module 413, for the facial image that face detection module described in pre-service 412 gets, utilizes homographic filtering method to carry out pre-service to facial image, to eliminate the impact of illumination.
Characteristic extracting module 414, for extracting the facial characteristics of people in described facial image.Extract face characteristic by Gabor transformation, and use LDA dimensionality reduction, obtain the feature that can reflect classification essence.
Face detection module 412 is connected to characteristic extracting module 414 by facial pretreatment module 412.
Server 1 comprises:
One database 11, for storing customer information, described customer information comprises client identity information and client's face feature information;
One training module 12, for extracting the face feature information of people and being stored to described database from image;
One Registering modules 13, for storing described customer information to described database, concurrent customer image of sending is to described training module;
One contrast module 14, for contrasting the client's face feature information in the face feature information of the described personnel through camera view and described database successively;
One client's determination module 15, for judging whether the described personnel through camera view have stored record in a database; If so, judge that the described personnel through camera view are as known customer, send the customer information of this known customer to described display; If not, judge that the described personnel through camera view are as unknown client, send result of determination to described display.
Registering modules 13 is connected to database 11, and for storing described customer information to database 11, Registering modules 13 is connected to database 11 by training module 12, for sending customer image to training module 12.Registering modules 13 utilizes the projector space of training module 12 to extract feature, stored in database 11.Registering modules utilizes the projector space of training module to extract feature, stored in database.User of the present invention can utilize Registering modules 13 to input in customer information to database of the present invention, described customer information comprises client identity information and client's mug shot etc. in correspondence with each other, client identity information directly can be stored to database, client's mug shot can first process through training module 12, is stored to database again after extracting the face feature information of this client.Training module 12 is off-line mode, carries out pre-service, feature extraction and selection successively to the picture in face database, obtains the feature that can reflect face classification essence, is saved in database 11.
Training module 12 comprises:
Face datection training module 121, for detecting in described image whether there is facial image, if so, obtains facial image, if not, detects next image.Check processing is carried out to described image, sorter training is carried out to the Harr feature of described image, obtain the boost sorter of a cascade, utilize this sorter to realize Face datection.
Facial pretreatment training module 122, for facial image described in pre-service, utilizes homographic filtering method to carry out pre-service to facial image, to eliminate the impact of illumination, angle.
Feature extraction training module 123, for extracting the feature of described face.Extract face characteristic data with Gabor ripple, and by LDA dimension-reduction treatment face characteristic data, obtain the characteristic that can reflect classification essence, decrease correlation data amount, improve work efficiency.
Face datection training module is connected to described feature extraction training module by described facial pretreatment training module.
Collection apparatus module 41, database 11 are connected to contrast module 14 respectively, and contrast module 14 is connected to client's determination module 15.
Described client identity recognition system also comprises a handheld terminal 5, is connected to described server by wireless network, for inputting and sending information to server 1, for showing described customer information and result of determination.
Server 1 also comprises a wireless communication module (not shown), and handheld terminal 5 comprises a corresponding wireless communication module (not shown), for realizing radio communication between described server and described handheld terminal.Handheld terminal comprises touch-screen; Or handheld terminal 5 comprises keyboard and display screen.
If the client come in gate inhibition place is known customer, reception personnel can obtain the identifying data of this client fast by uds server or handheld terminal, can call suitably the very first time, receive this client, with this Communication with Customer, and without the need to again registering the relevant information of client.
If the client come in gate inhibition place is unknown client, reception personnel can communicate with client in time, obtains its identity information, and utilizes uds server or handheld terminal to be stored by the database of its identity information input system.
A kind of client identity recognition methods as shown in Figure 2, comprises the steps:
Step (S1), arranges a display and at least one camera; Camera can be arranged on service location doorway, outdoors, foreground etc. position so that monitor staff can obtain monitor message quickly and easily in the very first time, described monitor message comprises the face feature information of personnel in each camera view.
Step (S2), gather customer information, described customer information comprises client identity information, client's face feature information and spending limit information etc.; This database data is comprehensive, and information completely, needs long-term collection process.
As shown in Figure 3, gather customer information, comprise the steps:
Step (S201), Registering modules stores client identity information to database;
Step (S202), described Registering modules sends customer image to training module;
Step (S203), described training module extracts client's face feature information and is stored to described database from described customer image.Described Registering modules utilizes the projector space of described training module to extract feature, stored in database.
Step (S3), gathers the face feature information of the described personnel through camera view; Utilize video camera to take the photo in this people front, from photo, find suitable unique point, be recorded as face feature information.
As shown in Figure 4, gather the face feature information of the described personnel through camera view, comprise the steps:
Step (S301), obtains the image of the described personnel through camera view;
Step (S302), detects in described image whether there is facial image, if not, detects next image, if so, obtains facial image;
Step (S303), facial image described in pre-service;
Step (S304), extracts the facial characteristics of people in described facial image.
Step (S4), contrasts the face feature information in the face feature information of the described personnel through camera view and the customer information of described database successively.
Step (S5), judges whether the described personnel through camera view have stored record in a database; If so, judge that the described personnel through camera view are as known customer, send this known customer information to display; If not, judge that the described personnel through camera view are as unknown client, send result of determination to described display or handheld terminal.
Described handheld terminal, is connected to described server by wireless network, for inputting and sending information to server, for showing described customer information and result of determination.Described handheld terminal comprises touch-screen; Or described handheld terminal comprises keyboard and display screen.
In use, it is known customer or unknown client that reception personnel can understand by the display very first time of server or handheld terminal the client come at gate inhibition place in the present invention.
If the client come in gate inhibition place is known customer, reception personnel can obtain the identifying data of this client fast by uds server or handheld terminal, can call suitably the very first time, receive this client, with this Communication with Customer, and without the need to again registering the relevant information of client.
If the client come in gate inhibition place is unknown client, reception personnel can communicate with client in time, obtains its identity information, and utilizes uds server or handheld terminal to be stored by the database of its identity information input system.
The foregoing is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, without departing from the inventive concept of the premise; can also make some improvements and modifications, these improvements and modifications also should be considered within the scope of protection of the present invention.
Claims (10)
1. a client identity recognition system, is characterized in that, comprising:
One server;
One display;
At least one camera, for taking image through the personnel of this camera view or video; And
At least one computing machine;
Each camera is connected to a computing machine, and each computing machine is connected to described server;
Each computing machine comprises a collection apparatus module, for gathering the face feature information of the described personnel through camera view;
Described server comprises:
One database, for storing customer information, described customer information comprises client identity information and client's face feature information;
One training module, for extracting the face feature information of people and being stored to described database from image;
One Registering modules, for storing described customer information to described database, concurrent customer image of sending is to described training module;
One contrast module, for contrasting the client's face feature information in the face feature information of the described personnel through camera view and described database successively;
One client's determination module, for judging whether the described personnel through camera view have stored record in a database; If so, judge that the described personnel through camera view are as known customer, send the customer information of this known customer to described display; If not, judge that the described personnel through camera view are as unknown client, send result of determination to described display.
2. client identity recognition system as claimed in claim 1, it is characterized in that, described collection apparatus module comprises:
Image collection module, for obtaining the image of the described personnel through camera view;
Face detection module, for whether there is facial image in detected image, if so, obtains facial image, if not, detects next image;
Facial pretreatment module, for facial image described in pre-service;
Characteristic extracting module, for extracting the facial characteristics of people in described facial image;
Described face detection module is by described facial pretreatment model calling extremely described characteristic extracting module.
3. client identity recognition system as claimed in claim 1, it is characterized in that, described training module comprises:
Face datection training module, for obtaining facial image;
Facial pretreatment training module, for facial image described in pre-service;
Feature extraction training module, for extracting the feature of described face;
Face datection training module is connected to described feature extraction training module by described facial pretreatment training module.
4. client identity recognition system as claimed in claim 1, it is characterized in that, described collection apparatus module, described database are connected to described contrast module respectively, and described contrast model calling is to described client's determination module.
5. client identity recognition system as claimed in claim 1, it is characterized in that, described Registering modules is connected to described database, and described Registering modules is connected to described database by training module.
6. client identity recognition system as claimed in claim 1, is characterized in that, also comprise a handheld terminal, be connected to described server by wireless network, for inputting and sending information to server, for showing described customer information and result of determination.
7. client identity recognition system as claimed in claim 6, it is characterized in that, described handheld terminal comprises touch-screen; Or described handheld terminal comprises keyboard and display screen.
8. a client identity recognition methods, is characterized in that, comprises the steps:
One display and at least one camera are set;
Gather customer information, described customer information comprises client identity information and client's face feature information;
Gather the face feature information of the described personnel through camera view;
Contrast the face feature information in the face feature information of the described personnel through camera view and the customer information of described database successively;
Judge whether the described personnel through camera view have stored record in a database; If so, judge that the described personnel through camera view are as known customer, send this known customer information to display; If not, judge that the described personnel through camera view are as unknown client, send result of determination to described display.
9. client identity recognition methods as claimed in claim 8, it is characterized in that, described collection customer information, comprises the steps:
Registering modules stores client identity information to database;
Described Registering modules sends customer image to training module;
Described training module extracts client's face feature information and is stored to described database from described customer image.
10. client identity recognition methods as claimed in claim 8, it is characterized in that, the face feature information of the described personnel through camera view of described collection, comprises the steps:
Obtain the image of the described personnel through camera view;
Detect in described image and whether there is facial image, if not, detect next image, if so, obtain facial image;
Facial image described in pre-service;
Extract the facial characteristics of people in described facial image.
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| CN106927324A (en) * | 2017-04-13 | 2017-07-07 | 安徽省沃瑞网络科技有限公司 | A kind of sales management method based on recognition of face |
| CN107392798A (en) * | 2017-08-11 | 2017-11-24 | 无锡北斗星通信息科技有限公司 | Restaurant's mixing system based on image recognition |
| CN107463915A (en) * | 2017-08-11 | 2017-12-12 | 无锡北斗星通信息科技有限公司 | A kind of restaurant's concocting method based on image recognition |
| CN108133533A (en) * | 2018-02-23 | 2018-06-08 | 王志强 | A kind of synthesis door meets management system |
| CN108696602A (en) * | 2018-05-15 | 2018-10-23 | 北京华大智宝电子系统有限公司 | A kind of client's recognition methods and system |
| CN109086665A (en) * | 2018-06-27 | 2018-12-25 | 相舆科技（上海）有限公司 | A kind of Management System for Clients Information based on recognition of face |
| CN109377251A (en) * | 2018-08-27 | 2019-02-22 | 广东履安实业有限公司 | A kind of method and system identifying client properties |
| CN109408676A (en) * | 2018-01-25 | 2019-03-01 | 维沃移动通信有限公司 | A kind of method and terminal device showing user information |
| CN109859401A (en) * | 2019-01-31 | 2019-06-07 | 杭州凡咖网络科技有限公司 | A kind of self-service coffee machine pattern recognition device and its operating method |
| CN109902661A (en) * | 2019-03-18 | 2019-06-18 | 北京联诚智胜信息技术股份有限公司 | Intelligent identification Method based on video, picture |
| CN109977645A (en) * | 2019-03-18 | 2019-07-05 | 咪付（广西）网络技术有限公司 | A kind of identification system |
| CN112188171A (en) * | 2020-09-30 | 2021-01-05 | 重庆天智慧启科技有限公司 | System and method for judging visiting relationship of client |
| CN113076295A (en) * | 2021-04-15 | 2021-07-06 | 泉州文学士信息科技有限公司 | Integrated customer information correlation synchronization system and device matched with same |
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| CN106927324A (en) * | 2017-04-13 | 2017-07-07 | 安徽省沃瑞网络科技有限公司 | A kind of sales management method based on recognition of face |
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| CN109859401A (en) * | 2019-01-31 | 2019-06-07 | 杭州凡咖网络科技有限公司 | A kind of self-service coffee machine pattern recognition device and its operating method |
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| CN109977645A (en) * | 2019-03-18 | 2019-07-05 | 咪付（广西）网络技术有限公司 | A kind of identification system |
| CN112188171A (en) * | 2020-09-30 | 2021-01-05 | 重庆天智慧启科技有限公司 | System and method for judging visiting relationship of client |
| CN113076295A (en) * | 2021-04-15 | 2021-07-06 | 泉州文学士信息科技有限公司 | Integrated customer information correlation synchronization system and device matched with same |
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Application publication date: 20160217 |