CN111708906A - Visiting retrieval method, device and equipment based on face recognition and storage medium - Google Patents
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Abstract
The invention provides a visiting retrieval method, a visiting retrieval device, visiting retrieval equipment and a storage medium based on face recognition, wherein the method comprises the following steps: shooting a face image according to a preset face recognition device, and establishing a plurality of face libraries in unit time according to the face image and based on shooting time; clustering and clearing the face library in unit time at regular time to obtain a processed face library in unit time; receiving target face image information and target time information; and selecting a corresponding target unit time face library from the processed unit time face libraries according to the target time information, starting a corresponding number of threads to simultaneously search each target unit face library to obtain a target face image matched with the target face image and shooting time, and establishing a visiting data set corresponding to the target face image according to the target face image and the shooting time. The scheme shortens the time consumption of clustering and clearing, and greatly improves the retrieval efficiency and the output accuracy.
Description
Technical Field
The invention relates to the technical field of computer communication, in particular to a visiting retrieval method, a visiting retrieval device, visiting retrieval equipment and a storage medium based on face recognition.
Background
In a traditional case face recognition wind control system, all face picture data are stored in a face library, face picture clustering is carried out on the library every day, and operations such as clearing of pictures which do not meet face recognition standards are carried out, and when a user uploads pictures and uses a visiting track retrieval function, the system outputs 10 most similar pictures and visiting time in the face library.
As time goes on, the face library capacity increases continuously: on one hand, the time consumption of the clustering and clearing tasks is longer and longer every day, and the system efficiency is greatly reduced; on the other hand, when track retrieval is carried out, the retrieval time is prolonged, the face misidentification rate is improved or the track is incomplete; finally, in order to ensure the system operation efficiency, the database cleaning operation is carried out even if the disk capacity is sufficient, such as periodically deleting the face image data 3 months to 6 months ago. Therefore, the time for retrieving the visiting track is longer and longer, so that the retrieval efficiency is low.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method, an apparatus, a device and a storage medium for visiting search based on face recognition.
A method for visiting retrieval based on face recognition, the method comprising: shooting a face image according to a preset face recognition device, and establishing a plurality of face libraries in unit time according to the face image and based on shooting time; clustering and clearing the face library in unit time at regular time to obtain a processed face library in unit time; receiving target face image information and target time information; and selecting a corresponding target unit time face library from the processed unit time face libraries according to the target time information, starting a corresponding number of threads to simultaneously retrieve each target unit face library to obtain a target face image matched with the target face image and shooting time, and establishing an access data set corresponding to the target face image according to the target face image and the shooting time.
In one embodiment, after the face image is shot according to a preset face recognition device, and before a plurality of face libraries in unit time are established based on shooting time according to the face image, the method further includes: establishing an employee face library, wherein the employee face library comprises face images of all employees; based on the face images of the employee face library, performing similarity comparison on the shot face images to obtain similarity; and when the similarity accords with a preset value, deleting the shot face image.
In one embodiment, the clustering and removing process is performed on the face library in unit time at regular time to obtain a processed face library in unit time, and specifically includes: calculating the similarity between all face images in the face library in unit time, and aggregating the face images with the similarity meeting a preset value into the same set; selecting a set with the number of face images larger than a preset value in the set as a target set; and based on the target set, selecting each face image in the target set according to the preselected characteristic factors, and deleting the face images which do not meet the preset standard, so as to obtain a processed face library in unit time.
In one embodiment, after the calculating the similarity between all the face images in the face library in unit time and aggregating the face images whose similarities meet a preset value into the same set, the method further includes: and (4) selecting the face images in each set one by one according to preselected characteristic factors, and selecting three images with the highest scores as the characteristic images of each set.
In one embodiment, after receiving the target face image information and the target time information, the method further includes: and carrying out standardization processing on the received target face image information to obtain a standardized target face image.
In one embodiment, the selecting, according to the target time information, a corresponding target unit-time face library from the processed unit-time face libraries, starting a corresponding number of threads to search each target unit-time face library simultaneously, obtaining a target face image and shooting time matched with the target face image, and after establishing an access data set corresponding to the target face image according to the target face image and the shooting time, further includes: and displaying the visiting data set corresponding to the target face image.
The utility model provides a visitor retrieval device based on face identification, includes and builds base module, processing module, receiving module and matching module, wherein: the database building module is used for shooting face images according to a preset face recognition device and building a plurality of face databases in unit time according to the face images and based on shooting time; the processing module is used for clustering and clearing the face library in unit time at regular time to obtain a processed face library in unit time; the receiving module is used for receiving target face image information and target time information; the matching module is used for selecting a corresponding target unit time face library from the processed unit time face libraries according to the target time information, starting a corresponding number of threads to simultaneously search each target unit face library to obtain a target face image and shooting time matched with the target face image, and establishing an access data set corresponding to the target face image according to the target face image and the shooting time.
In one embodiment, the apparatus further comprises a display module: and the display module is used for displaying the visiting data set corresponding to the target face image.
An apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the customer behavior analysis method described in the various embodiments above when executing the program.
A storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the customer behavior analysis method described in the various embodiments above.
According to the visiting retrieval method, the visiting retrieval device, the visiting retrieval equipment and the storage medium based on the face recognition, a plurality of face libraries in unit time are established based on shooting time, and the face libraries in each unit time are clustered and cleared once at regular time, so that the time consumption of clustering and clearing tasks is shortened; in the retrieval process, a plurality of threads simultaneously retrieve a plurality of target face libraries in unit time, so that the user does not need to regularly clean the face libraries for the retrieval efficiency, and captured face image data can be retained for a longer time; and multithreading simultaneous processing also greatly improves retrieval efficiency and output accuracy, so that the utilization rate of the disk is maximized.
Drawings
FIG. 1 is a schematic flow chart illustrating a method for retrieving a visit based on face recognition according to an embodiment;
FIG. 2 is a block diagram of an embodiment of a visiting retrieval device based on face recognition;
fig. 3 is an internal structural diagram of the device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings by way of specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In one embodiment, as shown in fig. 1, there is provided a visiting retrieval method based on face recognition, including the following steps:
s110, shooting the face image according to a preset face recognition device, and establishing a plurality of face libraries in unit time according to the face image and based on shooting time.
Specifically, the face recognition device is deployed in a case, where the face recognition device may be a high-definition camera or a high-speed photographing scanner, and the face recognition device may photograph a face image of a person in a photographing range of the face recognition device. The face recognition device uploads the shot face images to the server, the server classifies the face images based on shooting time after receiving the face images, and then a face library in unit time is established. Preferably, the face image library may be established in units of time of day, and the face library in unit time thus established brings pictures taken on the same day into the face library in unit time.
In one embodiment, after the face image is shot according to a preset face recognition device, before a plurality of face libraries per unit time are established based on shooting time according to the face image, the method further comprises the following steps: establishing an employee face library, wherein the employee face library comprises face images of all employees; based on the face images of the employee face library, performing similarity comparison on the shot face images to obtain similarity; and when the similarity accords with a preset value, deleting the shot face image. Specifically, firstly, an employee face library is established in the server, and face images of all employees are stored in the employee face library. When the face recognition device shoots a face image, the face image is transmitted to the server, the server calls all staff face images in the staff face library to be compared with the shot face image to obtain the similarity of each comparison, if the degree of acquaintance between one staff face image and the shot face image reaches a preset value, the shot face image is a staff corresponding to the staff face image and does not belong to a client, and the staff is deleted. Preferably, the preset value may be 80%, and if the similarity reaches 80%, the shot face image is deleted, and if the similarity is lower than 80%, the subsequent processing step of incorporating the face library in the unit time according to the shooting time is performed. Because the face recognition device cannot distinguish the client from the staff during shooting, the shot face images are screened once before being put in storage, so that the image quantity in the face library in unit time can be reduced, and the subsequent retrieval rate can be improved.
And S120, clustering and clearing the face library in unit time at regular time to obtain the processed face library in unit time.
Specifically, the established face library in unit time is clustered and cleared at regular time, because the face library in unit time is performed according to a time line, generally in units of days, after the face library in unit time is established, new face images cannot be put into the face library subsequently, the clustering and clearing process only needs to be performed once, and then the processed fiducials arranged according to time are put into the face library in unit time.
In one embodiment, the clustering and removing process is performed on the face library in unit time at regular time to obtain a processed face library in unit time, specifically: calculating the similarity between all face images in the face library in unit time, and aggregating the face images with the similarity meeting a preset value into the same set; selecting a set with the number of face images larger than a preset value in the set as a target set; and based on the target set, selecting each face image in the target set according to preselected characteristic factors, and deleting the face images which do not meet the preset standard, so as to obtain a processed unit-time face library. Specifically, similarity between every two face images in the face library in each unit time is calculated, and the face images with the similarity between every two being greater than a preset value are placed in the same face image set, wherein the preset value is preferably 90% of the similarity. Then the face library in unit time is the combination of a plurality of sets, and each set has at least one face image. And then counting the number of the face images in each set, and selecting the set with the number of the face images larger than two as a target set. Processing each selected target set, and selecting each face image in the target set according to preset characteristic factors, wherein the preset characteristic factors are definition, a snapshot angle and a shielding rate, and the definition is low, namely the focus is not accurate; the shooting angle difference is such as half face, large side face, large pitch angle and the like; and the high shielding rate, for example, the shielding rate of the face exceeds 55%, is deleted.
In one embodiment, the step of calculating the similarity between all face images in the face library in unit time, and after aggregating the face images whose similarities meet a preset value into the same set, further includes: and (4) selecting the face images in each set one by one according to preselected characteristic factors, and selecting three images with the highest scores as the characteristic images of each set. Specifically, each face image in each set is evaluated one by one according to preselected characteristic factors, wherein the preselected characteristic factors are definition, a snapshot angle and a shielding rate, three face images with high overall definition, good snapshot angle and minimum shielding rate are selected to serve as characteristic images of the set, and when retrieval is carried out subsequently, the characteristic images of each set are directly used for comparison, if the images are consistent, the sets are directly selected, and the accuracy and the efficiency of the retrieval are improved to a certain extent.
S130 receives the target face image information and the target time information.
Specifically, the user inputs target face image information of a client who needs to retrieve a visiting track, and target time information. The target face image information is a customer photo of the visiting track needing to be searched, and the target time information is a time period needing to be searched.
In one embodiment, after step S130, the method further includes: and carrying out standardization processing on the received target face image information to obtain a standardized target face image. Specifically, the received target face image information needs to be processed, and preferably, the picture is subjected to base64 coding, so that data transmission is facilitated.
S140, according to the target time information, selecting a corresponding target unit time face library from the processed unit time face libraries, starting a corresponding number of threads to simultaneously search each target unit face library to obtain a target face image matched with the target face image and shooting time, and establishing a visiting data set corresponding to the target face image according to the target face image and the shooting time.
Specifically, according to target time information, selecting a unit time face library in a target time information range as a target unit time face library, then starting threads with corresponding number according to the number of the selected target unit time face libraries, and simultaneously retrieving a plurality of selected target unit time face libraries; thereby obtaining a target face image matched with the target face image and the shooting time of the target face image in each target unit time face library; and finally, establishing a visiting data set corresponding to the target face image according to the target face image and the shooting time.
In one embodiment, after step S140, the method further includes: and displaying the visiting data set corresponding to the target face image. Specifically, after the visiting data set of the target face image in the target time range is obtained in step S140, the data set is correspondingly displayed according to the time sequence.
In the embodiment, the face libraries in the unit time are established based on the shooting time, and the clustering and clearing process is performed once only after each face library in the unit time is established, so that the time consumption of clustering and clearing tasks is shortened; in the retrieval process, a plurality of threads simultaneously retrieve a plurality of target face libraries in unit time, so that the user does not need to regularly clean the face libraries for the retrieval efficiency, and captured face image data can be retained for a longer time; and multithreading simultaneous processing also greatly improves retrieval efficiency and output accuracy, so that the utilization rate of the disk is maximized.
In one embodiment, as shown in fig. 2, there is provided a visiting retrieval device 200 based on face recognition, the device comprising a library building module 201, a processing module 202, a receiving module 203 and a matching module 204, wherein:
the database building module 201 is used for shooting face images according to a preset face recognition device and building a plurality of face databases in unit time according to the face images and based on shooting time;
the processing module 202 is configured to perform clustering and removing processing on the face library in unit time at regular time to obtain a processed face library in unit time;
the receiving module 203 is configured to receive target face image information and target time information;
the matching module 204 is configured to select a corresponding target unit-time face library from the processed unit-time face libraries according to the target time information, start a corresponding number of threads to search each target unit face library simultaneously, obtain a target face image and shooting time that are matched with the target face image, and establish an access data set corresponding to the target face image according to the target face image and the shooting time.
In one embodiment, the database building module 201 is further configured to build an employee face database, where the employee face database includes face images of all employees; based on the face images of the employee face library, performing similarity comparison on the shot face images to obtain similarity; and when the similarity accords with a preset value, deleting the shot face image.
In one embodiment, the processing module 202 is further configured to calculate similarities between all face images in the face library in unit time, and aggregate the face images whose similarities meet a preset value into the same set; selecting a set with the number of face images larger than a preset value in the set as a target set; and based on the target set, selecting each face image in the target set according to preselected characteristic factors, and deleting the face images which do not meet the preset standard, so as to obtain a processed unit-time face library.
In one embodiment, the processing module 202 is further configured to select the face images in each set one by one according to preselected feature factors, and select the three images with the highest scores as the feature images of each set.
In one embodiment, the apparatus further comprises a normalization module, wherein: and the standardization module is used for carrying out standardization processing on the received target face image information to obtain a standardized target face image.
In one embodiment, the apparatus further comprises a display module, wherein: the display module is used for displaying the visiting data set corresponding to the target face image.
In one embodiment, a device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 3. The device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the device is configured to provide computing and control capabilities. The memory of the device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the device is used for storing configuration templates and also can be used for storing target webpage data. The network interface of the device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method for visiting retrieval based on face recognition.
Those skilled in the art will appreciate that the configuration shown in fig. 3 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation on the devices to which the present application may be applied, and that a particular device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, a storage medium is further provided, which stores a computer program comprising program instructions, which when executed by a computer, which may be part of the above mentioned face recognition based visiting retrieval device, cause the computer to perform the method according to the previous embodiment.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
It will be apparent to those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented in program code executable by a computing device, such that they may be stored on a computer storage medium (ROM/RAM, magnetic disks, optical disks) and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a more detailed description of the present invention that is presented in conjunction with specific embodiments, and the practice of the invention is not to be considered limited to those descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. A visiting retrieval method based on face recognition is characterized by comprising the following steps:
shooting a face image according to a preset face recognition device, and establishing a plurality of face libraries in unit time according to the face image and based on shooting time;
clustering and clearing the face library in unit time at regular time to obtain a processed face library in unit time;
receiving target face image information and target time information;
and selecting a corresponding target unit time face library from the processed unit time face libraries according to the target time information, starting a corresponding number of threads to simultaneously retrieve each target unit face library to obtain a target face image matched with the target face image and shooting time, and establishing an access data set corresponding to the target face image according to the target face image and the shooting time.
2. The method as claimed in claim 1, wherein after the face image is photographed according to a preset face recognition device, and before the face image is photographed according to the preset face recognition device and before the face image is photographed based on photographing time, the method further comprises:
establishing an employee face library, wherein the employee face library comprises face images of all employees;
based on the face images of the employee face library, performing similarity comparison on the shot face images to obtain similarity;
and when the similarity accords with a preset value, deleting the shot face image.
3. The method according to claim 1, wherein the clustering and cleaning process is performed on the face library in unit time at regular time to obtain a processed face library in unit time, specifically:
calculating the similarity between all face images in the face library in unit time, and aggregating the face images with the similarity meeting a preset value into the same set;
selecting a set with the number of face images larger than a preset value in the set as a target set;
and based on the target set, selecting each face image in the target set according to the preselected characteristic factors, and deleting the face images which do not meet the preset standard, so as to obtain a processed face library in unit time.
4. The method of claim 3, wherein after calculating the similarity between all the face images in the face library in unit time and aggregating the face images with the similarity meeting a preset value into the same set, the method further comprises:
and (4) selecting the face images in each set one by one according to preselected characteristic factors, and selecting three images with the highest scores as the characteristic images of each set.
5. The method of claim 1, wherein after receiving the target face image information and the target time information, further comprising:
and carrying out standardization processing on the received target face image information to obtain a standardized target face image.
6. The method as claimed in claim 1, wherein the selecting a corresponding target unit time face library from the processed unit time face libraries according to the target time information, starting a corresponding number of threads to search each target unit face library simultaneously, obtaining a target face image and a shooting time matched with the target face image, and after establishing a visiting data set corresponding to the target face image according to the target face image and the shooting time, further comprising:
and displaying the visiting data set corresponding to the target face image.
7. The utility model provides a visitor retrieval device based on face identification which characterized in that, includes and builds library module, processing module, receiving module and matching module, wherein:
the database building module is used for shooting face images according to a preset face recognition device and building a plurality of face databases in unit time according to the face images and based on shooting time;
the processing module is used for clustering and clearing the face library in unit time at regular time to obtain a processed face library in unit time;
the receiving module is used for receiving target face image information and target time information;
the matching module is used for selecting a corresponding target unit time face library from the processed unit time face libraries according to the target time information, starting a corresponding number of threads to simultaneously search each target unit face library to obtain a target face image and shooting time matched with the target face image, and establishing an access data set corresponding to the target face image according to the target face image and the shooting time.
8. The apparatus of claim 7, further comprising a display module:
and the display module is used for displaying the visiting data set corresponding to the target face image.
9. An apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 6 are implemented when the computer program is executed by the processor.
10. A storage medium having a computer program stored thereon, the computer program, when being executed by a processor, realizing the steps of the method of any one of claims 1 to 6.
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| CN109815775A (en) * | 2017-11-22 | 2019-05-28 | 深圳市祈飞科技有限公司 | A kind of face identification method and system based on face character |
| CN109727411A (en) * | 2018-12-13 | 2019-05-07 | 广州万升信息科技有限公司 | It is authenticated based on recognition of face, barcode scanning, the book borrowing system of human body sensing |
| CN109597908A (en) * | 2018-12-14 | 2019-04-09 | 深圳壹账通智能科技有限公司 | Photo searching method, device, equipment and storage medium based on recognition of face |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112836660A (en) * | 2021-02-08 | 2021-05-25 | 上海卓繁信息技术股份有限公司 | Face library generation method and device for monitoring field and electronic equipment |
| CN112861834A (en) * | 2021-04-26 | 2021-05-28 | 北京京安佳新技术有限公司 | Communication information acquisition method based on base station data |
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