CN114140856A - Face recognition method, device, system, computer equipment and readable storage medium - Google Patents
Face recognition method, device, system, computer equipment and readable storage medium Download PDFInfo
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- G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
- G07C9/25—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
- G07C9/26—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition using a biometric sensor integrated in the pass
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Abstract
The invention provides a face recognition method, a face recognition device, a face recognition system, computer equipment and a readable storage medium. The face recognition method comprises the following steps: reading a tag signal of an electronic tag carried by a target user, wherein the electronic tag is bound with the target user; acquiring a face comparison characteristic corresponding to the label signal; acquiring a face image of the target user; matching the feature data of the face image of the target user with the face comparison feature; and determining a face recognition result according to the matching result. By the method and the device, resource consumption in the face recognition process can be reduced.
Description
Technical Field
The invention relates to the technical field of intelligent buildings, in particular to a face recognition method, a face recognition device, a face recognition system, computer equipment and a readable storage medium.
Background
With the acceleration of informatization of the building industry, more and more construction sites adopt the biological recognition technology, adopt the computer to obtain workman's information, synchronous to the face terminal after gathering the close-up, come managers to pass in and out the job site through face recognition technology. The process of matching and identifying the face image is that the extracted feature data of the face image is searched and matched with a feature template stored in a database, and a threshold value is set, and when the similarity exceeds the threshold value, the result obtained by matching is output.
The inventor researches and discovers that when the feature data of the extracted face image is compared with the feature templates stored in the database, a pair of matching of all the feature templates is generally performed, that is, in the process of face recognition, the face features of a worker to enter are required to be compared with the N feature templates stored in the database one by one to form a 1: n image matching modality. However, when the project size is large, the number N of worker feature templates in the database is also large. When more than N people are in ten thousand, the characteristic value of one person needs to be extracted and compared with the characteristic values of more than ten thousand people one by one, and whether the person is the closest person can be found for judgment or not. At this time, the problems of obvious reduction of equipment performance, slow reaction, reduction of commuting efficiency and the like exist, and the larger N is, the higher the performance requirement of the product is. Therefore, the whole face recognition process has high equipment configuration, large memory, great influence on the performance of the whole product and very high resource consumption.
Therefore, how to reduce the resource consumption in the face recognition process becomes a technical problem to be solved urgently in the field.
Disclosure of Invention
The present invention is directed to a face recognition method, apparatus, system, computer device and readable storage medium, which are used to solve the above technical problems in the prior art.
In one aspect, the present invention provides a face recognition method for achieving the above-mentioned objects.
The face recognition method comprises the following steps: reading a tag signal of an electronic tag carried by a target user, wherein the electronic tag is bound with the target user; acquiring a face comparison characteristic corresponding to the label signal; acquiring a face image of the target user; matching the feature data of the face image of the target user with the face comparison feature; and determining a face recognition result according to the matching result.
Further, the electronic tag is a UHF electronic tag arranged on the safety helmet.
Further, the tag signal includes identification information of a safety helmet, and the step of obtaining the face comparison feature corresponding to the tag signal includes: analyzing the label signal to obtain the identification information of the safety helmet; and searching the face comparison characteristics corresponding to the identification information in a sample database.
Further, the face recognition method further comprises the following steps: receiving user personal information, wherein the user personal information comprises identification information of a safety helmet; acquiring a face image of a user to obtain a plurality of face image samples; calculating the face comparison characteristics according to the face image samples; and storing the identification information and the face comparison characteristics to the sample database.
Further, the step of obtaining the face comparison characteristics corresponding to the tag signal further includes, after the step of analyzing the tag signal to obtain the identification information of the safety helmet and before searching the face comparison characteristics corresponding to the identification information in a sample database, the step of obtaining the face comparison characteristics corresponding to the tag signal further includes: searching the face comparison times corresponding to the identification information in the sample database; the step of searching the face comparison characteristics corresponding to the identification information in the sample database comprises the following steps: when the face comparison times meet a preset requirement, searching a face comparison characteristic corresponding to the identification information in a sample database; the face recognition method further comprises the following steps: and when the face comparison times do not meet the preset requirement, outputting prompt information for identifying overrun.
Further, the face recognition method further comprises: and after searching the face comparison characteristics corresponding to the identification information in a sample database, subtracting 1 from the face comparison times corresponding to the identification information, wherein the initial value of the face comparison times is a face comparison time threshold.
In another aspect, the present invention provides a face recognition apparatus for achieving the above object.
The face recognition device includes: the reading module is used for reading a tag signal of an electronic tag carried by a target user, wherein the electronic tag is bound with the target user; the acquisition module is used for acquiring the face comparison characteristics corresponding to the label signals; the acquisition module is used for acquiring the face image of the target user; the matching module is used for matching the feature data of the face image with the comparison feature; and the determining module is used for determining a face recognition result according to the matching result.
In another aspect, the present invention provides a face recognition system for achieving the above objects.
The face recognition system includes: electronic tags, signal reading module, control module group and image acquisition module, wherein: the electronic tag is used for generating a tag signal, wherein the electronic tag is bound with the target user; the signal reading module is used for reading the label signal; the image acquisition module is used for acquiring a face image of a target user; the control module is used for acquiring a face comparison characteristic corresponding to the label signal, matching the characteristic data of the face image with the comparison characteristic, and determining a face recognition result according to a matching result.
In another aspect, to achieve the above object, the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of the method are implemented.
In another aspect, to achieve the above object, the present invention further provides a computer-readable storage medium having stored thereon a computer program, which when executed by a processor, performs the steps of the above method.
The face recognition method, the device, the system, the computer equipment and the readable storage medium provided by the invention utilize the label signal generated by the electronic label bound with the target user to be recognized to identify the target user to be recognized, and the human face comparison characteristic based on the label signal is preset, so that when the user to be identified is identified, the label signal of the electronic label carried by the user is read, the corresponding face comparison characteristics can be obtained according to the label signals, which is equivalent to that the face template to be matched is selected before the characteristic data of the face image of the user is matched, and the matching with all the face templates is not needed, so that only the feature data of the face image of the target user to be recognized needs to be matched with the acquired face comparison features, therefore, the resource consumption required by the matching process can be reduced, the matching efficiency is improved, and the face recognition efficiency is improved.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart of a face recognition method according to an embodiment of the present invention;
fig. 2 is a block diagram of a face recognition apparatus according to a second embodiment of the present invention;
fig. 3 is a block diagram of a face recognition system according to a third embodiment of the present invention;
fig. 4 is a schematic view of a work flow of a face recognition system according to a third embodiment of the present invention; and
fig. 5 is a hardware configuration diagram of a computer device according to a fourth embodiment of the present invention.
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 and 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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to reduce resource consumption in the process of face recognition, the invention provides a face recognition method, a device, a system, computer equipment and a readable storage medium, which are applied to managing access of constructors to a construction site in construction sites such as the field of buildings, wherein the constructors can access the construction site when face recognition is passed, otherwise, access is forbidden. Specifically, an electronic tag can be arranged on equipment which is convenient for a user to carry, a tag signal can be generated, and the electronic tag is bound with the user and can serve the purpose of identifying the user. A signal reading module capable of reading electronic tag signals is arranged at an entrance and an exit of a construction site. When a target user passes through an entrance, on one hand, a tag signal of an electronic tag carried by the target user is read, corresponding face comparison characteristics are obtained through the tag signal, on the other hand, a face image of the target user is collected, characteristic data of the face image is calculated, then the characteristic data is matched with the face comparison characteristics, a face recognition result is determined according to the matching result, and whether the target user is allowed to pass through the entrance or the exit is determined according to the recognition result. It can be seen that, in the invention, the characteristic data of the face image of the target user does not need to be compared with all face comparison characteristics, but the face comparison characteristics corresponding to the target user are obtained through the tag signal of the electronic tag based on the binding relationship between the electronic tag and the target user, and the comparison template of the characteristic data of the face image is reduced, so that the comparison speed can be improved, the response of face recognition is further improved, the commuting efficiency is improved, and the resource consumption is reduced due to the requirement of the face recognition process on equipment configuration.
Specific embodiments of the face recognition method, the face recognition apparatus, the face recognition system, the computer device, and the readable storage medium according to the present invention will be described in detail below.
Example one
The embodiment of the invention provides a face recognition method which can be applied to scenes with face recognition results as permission judgment conditions, such as construction sites and the like. By the method, resource consumption in the face recognition process can be reduced. Specifically, fig. 1 is a flowchart of a face recognition method according to an embodiment of the present invention, and as shown in fig. 1, the face recognition method according to the embodiment includes steps S101 to S105 as follows.
Step S101: and reading a tag signal of an electronic tag carried by a target user.
Wherein, the electronic tag is bound with the target user.
Specifically, the electronic tag carried by the target user is bound to the target user, that is, the electronic tag corresponds to the target user one to one. In one application scenario, the electronic tag may be assigned to a target user in advance, and accordingly, a tag signal generated by the electronic tag becomes a feature identifier of the target user.
Optionally, the electronic tag is disposed in equipment that is convenient for a user to carry, for example, in some conventional office scenes, the electronic tag may be disposed in a work card of a worker, or in some construction sites, the electronic tag may be disposed on a safety helmet of a construction worker, or in some high-altitude work scenes, the electronic tag may be disposed on a safety belt of a worker.
No matter what type of equipment the electronic tag is arranged in, when the user wears the equipment, the electronic tag arranged on the equipment is carried. Therefore, when a user wearing the equipment wants to pass through the inlet and the outlet of the signal reading module, the signal reading module can read the tag signal of the electronic tag carried by the user.
Step S102: and acquiring the face comparison characteristics corresponding to the label signals.
When the database for face recognition comprises more face templates, the label signal can be used as a key, the face template can be used as a value, and the face comparison characteristics are stored in a key-value pair mode. After the tag signal is obtained in step S102, the corresponding face comparison feature can be obtained through the tag signal. The label signal is used as the identification feature of the user, and the corresponding face comparison feature is also the face comparison feature of the corresponding user.
Step S103: and acquiring a face image of the target user.
When a target user wants to pass through the inlet and outlet of the image acquisition module, the image acquisition module acquires a face image of the target user, and after the face image is acquired, feature data of the face image can be calculated according to a preset face feature calculation method.
Step S104: and matching the feature data of the face image of the target user with the face comparison features.
In this step, the feature data of the face image to be recognized only needs to be matched with the acquired face comparison features, and any matching method in the prior art may be specifically adopted, which is not repeated here.
Optionally, the similarity between the feature data of the face image and the face comparison feature is calculated during matching, when the similarity is greater than or equal to a similarity threshold, it is indicated that the feature data of the face image is successfully matched with the face comparison feature, and when the similarity is less than a preset similarity threshold, it is indicated that the feature data of the face image is unsuccessfully matched with the face comparison feature.
Step S105: and determining a face recognition result according to the matching result.
Specifically, when the matching is successful, that is, the face recognition is passed, it is determined that the target user satisfies the authority requirement, and when the matching is failed, that is, the face recognition is different, it is determined that the target user does not satisfy the authority requirement.
By adopting the face recognition method provided by the embodiment, the target user to be recognized is identified by utilizing the tag signal generated by the electronic tag bound with the target user to be recognized, and the face comparison characteristic based on the tag signal is preset, so that when the user to be recognized is recognized, the tag signal of the electronic tag carried by the user is read, the corresponding face comparison characteristic can be obtained according to the tag signal, namely, the face template to be matched is selected before the characteristic data of the face image of the user is matched, and the matching with all the face templates is not needed, so that the characteristic data of the face image of the target user to be recognized only needs to be matched with the obtained face comparison characteristic, the resource consumption required in the matching process can be reduced, the matching efficiency is improved, and the face recognition efficiency is improved.
Optionally, in an embodiment, the electronic tag is a UHF electronic tag disposed on the helmet.
Particularly, can set up electronic tags on the safety helmet, can make the user noninductive carry, promote user experience to set up on the safety helmet, make things convenient for the signal to read the tag signal that the module produced of electronic tags. Meanwhile, a UHF electronic tag is adopted, belongs to one of RFID electronic tags, belongs to a passive electronic tag, and is a passive ultrahigh frequency radio frequency identification transponder. When the electronic tag is out of the reading range of the reader, the electronic tag is in a passive state, and when the electronic tag is in the reading range of the reader, the electronic tag extracts a power supply required by the work of the electronic tag from radio frequency energy emitted by the reader. The passive electronic tags generally adopt a reflection modulation mode to complete the transmission of electronic tag information to a reader. The working frequency is full band 860-960 MHz. The module has low power consumption, small volume and good RF performance, and is suitable for being arranged on a safety helmet.
Optionally, in an embodiment, the tag signal includes identification information of a safety helmet, and the step of obtaining a face comparison feature corresponding to the tag signal includes: analyzing the label signal to obtain the identification information of the safety helmet; and searching the face comparison characteristics corresponding to the identification information in the sample database.
Specifically, the safety helmet can be numbered as identification information, the identification information is encapsulated in the tag signal, and the identification information of the safety helmet and the face comparison feature of the user wearing the safety helmet are correspondingly stored in the sample database. When the face comparison characteristics corresponding to the label signals need to be acquired in the face recognition process, the read identification information of the safety helmet in the label signals is firstly analyzed, and then data searching is carried out in a sample database so as to search the face comparison characteristics corresponding to the representation information. The identification codes corresponding to the service types of the users, the working hours and the like can be set as identification information of the safety helmet, for example, the identification code corresponding to the service type X is identification X, the identification code corresponding to the service type Y comprises identification Y, the identification code corresponding to the work in the morning is identification P, the identification code corresponding to the work in the afternoon is identification a, and the sequence codes of the safety helmet are 001, 002, 003 and the like which are sequentially arranged.
By adopting the face recognition method provided by the embodiment, the label signal is formed based on the identification information of the safety helmet, and when the face comparison characteristic is obtained, the face comparison characteristic corresponding to the identification information is inquired from the sample database, so that the safety helmet is conveniently managed, and the speed of inquiring the face comparison characteristic is increased.
Optionally, in an embodiment, the face recognition method further includes: receiving user personal information, wherein the user personal information comprises identification information of a safety helmet; acquiring a face image of a user to obtain a plurality of face image samples; calculating face comparison characteristics according to a plurality of face image samples; and storing the identification information and the face comparison characteristics into a sample database.
Specifically, when the electronic tag is bound with a user, after the user selects a certain safety helmet, the personal information is registered first, and the identification information of the safety helmet is input to the information registration platform as the personal information of the user, that is, the electronic tag is bound with the user. At this time, the face image of the user can be synchronously acquired, specifically, image acquisition can be performed based on different angles to obtain a plurality of face image samples, the face comparison characteristics of the user are obtained by calculating the face image samples, and finally, the identification information and the face comparison characteristics in the personal information are correspondingly stored in a sample database.
By adopting the face recognition method provided by the embodiment, for the user, the binding of the electronic tag and the user and the acquisition and storage of the face comparison characteristics can be completed only by performing personal information registration after the safety helmet is selected, the operation is convenient, and the user experience is good.
Optionally, in an embodiment, the personal information of the user further includes a face comparison number, and after the step of analyzing the tag signal to obtain the identification information of the safety helmet, and before searching for the face comparison feature corresponding to the identification information in the sample database, the step of obtaining the face comparison feature corresponding to the tag signal further includes: searching the face comparison times corresponding to the identification information in a sample database; the step of searching the face comparison characteristics corresponding to the identification information in the sample database comprises the following steps: when the face comparison times meet a preset requirement, searching a face comparison characteristic corresponding to the identification information in a sample database; the face recognition method further comprises the following steps: and when the face comparison times do not meet the preset requirement, outputting prompt information for identifying the overrun.
Specifically, in some scenes, the number of times of use of the face recognition authority needs to be controlled, for example, a certain scene is only allowed to enter and exit once when a face recognition result is successful, in order to solve the problem, the face comparison number is also set in the sample database corresponding to the identification information, so that after the identification information is obtained, the corresponding face comparison number is searched first, and only when the face comparison number meets a preset requirement, the face comparison feature can be further searched, and then comparison matching is performed; if the searched face comparison times do not meet the preset requirements, the face comparison features cannot be searched, prompt information is output, the exceeding is prompted, and comparison and matching are not carried out any more. For example, the face comparison times are set according to the access authority times of a person, the initial value of the face comparison times is set to be 0, when the person accesses the system once through face recognition, the face comparison times are increased by 1, and when the face comparison times reach the authority times, the face comparison times cannot be searched in the face recognition process, so that the face recognition cannot be carried out any more, and the access authority times are limited.
By adopting the face recognition method provided by the embodiment, the number of face comparison corresponding to the identification information is set in the sample database, so that the limit on the number of face recognition detection times can be realized.
Optionally, in an embodiment, the face recognition method further includes: and after searching the face comparison characteristics corresponding to the identification information in the sample database, subtracting 1 from the face comparison times corresponding to the identification information, wherein the initial value of the face comparison times is a face comparison time threshold.
Specifically, the face comparison frequency threshold value can be configured as an initial value of the face comparison frequency, in the face recognition process, after identification information is obtained, the corresponding face comparison frequency is searched, when the face comparison frequency is greater than or equal to 1, the face comparison feature can be further searched, comparison matching is performed, and at the same time, the face comparison frequency is reduced by 1 every time the face comparison feature is searched; if the number of times of the searched face comparison is equal to 0, the face comparison feature cannot be searched.
By adopting the face recognition method provided by the embodiment, the face comparison time threshold is configured to be the initial value of the face comparison time, in the face recognition process, one face comparison feature is extracted, and the face comparison time is reduced by 1, so that even if different face comparison time thresholds are configured based on different persons, the search logics of the face comparison features are consistent, the different face recognition times can be processed by the configuration of the initial value of the face comparison time, the processing logics are consistent, and the speed is high.
Example two
Corresponding to the first embodiment, the second embodiment of the present invention provides a face recognition apparatus, and accordingly, reference may be made to the first embodiment for details of technical features and corresponding technical effects, which are not described in detail in this embodiment. Fig. 2 is a block diagram of a face recognition apparatus according to a second embodiment of the present invention, and as shown in fig. 2, the apparatus includes: a reading module 201, an obtaining module 202, a first acquisition module 203, a matching module 204 and a determination module 205.
The reading module 201 is configured to read identification information of an electronic tag carried by a target user; the obtaining module 202 is configured to obtain a face comparison feature corresponding to the tag signal; the first acquisition module 203 is used for acquiring a face image of the target user; the matching module 204 is configured to match the feature data of the face image with the comparison feature; the determining module 205 is configured to determine a face recognition result according to the matching result.
Optionally, in an embodiment, the electronic tag is a UHF electronic tag disposed on a helmet.
Optionally, in an embodiment, the tag signal includes identification information of a safety helmet, and the obtaining module includes: the analyzing unit is used for analyzing the label signal to obtain the identification information of the safety helmet; and the first searching unit is used for searching the face comparison characteristics corresponding to the identification information in the sample database.
Optionally, in an embodiment, the face recognition apparatus further includes: the system comprises a receiving module, a judging module and a display module, wherein the receiving module is used for receiving user personal information, and the user personal information comprises identification information of a safety helmet; the second acquisition module is used for acquiring the face images of the user to obtain a plurality of face image samples; the calculation module is used for calculating the face comparison characteristics according to the face image samples; and the storage module is used for storing the identification information and the face comparison characteristics to the sample database.
Optionally, in an embodiment, the user personal information further includes a face comparison number, and the obtaining module further includes: the second searching unit is used for searching the face comparison times corresponding to the identification information in the sample database before the first searching unit searches the face comparison characteristics corresponding to the identification information in the sample database after the step of analyzing the label signal by the analyzing unit to obtain the identification information of the safety helmet; the first searching unit is further used for searching the face comparison characteristics corresponding to the identification information in the sample database when the face comparison times meet a preset requirement; the face recognition apparatus further includes: and the output module is used for outputting prompt information for identifying the overrun when the face comparison times do not meet the preset requirement.
The face recognition apparatus further includes: and the processing module is used for subtracting 1 from the face comparison times corresponding to the identification information after the first searching unit searches the face comparison characteristics corresponding to the identification information in the sample database, wherein the initial value of the face comparison times is a face comparison time threshold.
EXAMPLE III
Corresponding to the first embodiment, a third embodiment of the present invention provides a face recognition system, and reference may be made to the first embodiment for details of technical features and corresponding technical effects, which are not described in detail in this embodiment. Fig. 3 is a block diagram of a face recognition system according to a third embodiment of the present invention, where the face recognition system includes an electronic tag 301, a signal reading module 302, a control module 303, and a first image capturing module 304.
Wherein, the electronic tag 301 is used for generating a tag signal; the signal reading module 302 is configured to read the tag signal; the first image acquisition module 304 is configured to acquire a face image of a target user; the control module 303 is configured to obtain a face comparison feature corresponding to the tag signal, match feature data of the face image with the comparison feature, and determine a face recognition result according to a matching result.
Optionally, in an embodiment, the electronic tag is a UHF electronic tag disposed on the helmet, and the signal reading module is a UHF card reader.
Optionally, in an embodiment, the tag signal includes identification information of a safety helmet, and when the control module acquires a face comparison feature corresponding to the tag signal, the specifically executed step includes: analyzing the label signal to obtain the identification information of the safety helmet; and searching the face comparison characteristics corresponding to the identification information in a sample database.
Optionally, in an embodiment, the face recognition system further includes a management platform and a second image acquisition module, wherein the management platform is configured to receive personal information of a user, the personal information of the user includes identification information of a safety helmet, the second image acquisition module is configured to acquire a face image of the user to obtain a plurality of face image samples, and the management slip is further configured to calculate the face comparison feature according to the plurality of face image samples, and store the identification information and the face comparison feature in the sample database.
Optionally, in an embodiment, the personal information of the user further includes a face comparison number, and the control module is further configured to, after the step of analyzing the tag signal to obtain the identification information of the helmet, search for the face comparison number corresponding to the identification information in a sample database before searching for the face comparison feature corresponding to the identification information in the sample database; when the control module searches the face comparison characteristics corresponding to the identification information in the sample database, the specifically executed steps comprise: when the face comparison times meet a preset requirement, searching a face comparison characteristic corresponding to the identification information in a sample database; the face recognition system further comprises an information output module used for outputting prompt information for recognizing the overrun when the face comparison times do not meet the preset requirements.
Optionally, in an embodiment, the control module is further configured to subtract 1 from the face comparison times corresponding to the identification information after searching for the face comparison feature corresponding to the identification information in the sample database, where an initial value of the face comparison times is a face comparison time threshold.
Optionally, in an embodiment, the face recognition system includes a self-service boarding machine, a helmet provided with an electronic tag, and a gate, a card reader, a control panel and a camera device provided at an entrance and an exit. Fig. 4 is a schematic view of a work flow of the face recognition system according to the third embodiment of the present invention, and as shown in fig. 4, a worker first completes the binding of the integrated helmet through steps of reading an identity card, self-service face registration and warehousing, self-service helmet pickup, binding, and the like. When a worker passes through the gate, an integrated UHF card reader (UHF-reader) in the control panel reads the UHF electronic tag number installed on the hat and directly retrieves the characteristic value of the worker from the database. Meanwhile, after the camera device collects the close shot of a worker, the close shot is synchronized to the control panel, the face characteristic value is extracted through the image recognition technology, the extracted characteristic data of the face image and the characteristic template called from the library by reading the UHF electronic tag are subjected to image matching comparison, and the identity information of the face is judged according to the similarity degree. And setting a passing threshold, and when the similarity exceeds the threshold, identifying the identity of a worker, opening a gate and allowing the passage.
The passing threshold is preset to be 90, and can be manually adjusted, wherein the passing threshold is a threshold for comparing pre-recorded face information with face information collected at the gate, if the comparison score is greater than the threshold, the same person is considered, the comparison is successful, and the gate is opened. Otherwise, the comparison fails, if the threshold value needs to be modified, the threshold value can be modified through the threshold value modification page, and the implementing personnel can judge and adjust the threshold value according to the actual condition and experience of the current environment.
Optionally, in some attendance scenes, an attendance time interval may be set, which is an interval for the same person to perform face recognition, that is, the same person can only check attendance once in the time interval. Optionally, the door opening duration is set, namely the time from the opening to the closing of the gate, when the face attendance is successful, the gate is opened, and the gate is called to be closed after the door opening duration.
Adopt the face identification system that this embodiment provided, equipment commute efficiency promotes, matches 1 in the face identification process: n turns to match 1: 1, when a worker passes through the gate, the UHF card number on the cap is read first, the characteristic value of the worker is directly called from the database without being compared one by one in the database, the efficiency is obviously improved, the performance requirement of the equipment is reduced, and the commuting efficiency of the equipment is improved. Meanwhile, on the basis of face attendance recording, due to the fact that the face and the cap are integrally bound, safety cap attendance data are added to be used as check, the data are more accurate, and double attendance recording is formed. Personnel verification through the man-cap all-in-one machine ensures that statistics of various types of work of field labor force is more accurate, and reduces the interference of mixed safety helmet bands.
Example four
The fourth embodiment further provides a computer device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a rack server (including an independent server or a server cluster composed of a plurality of servers) capable of executing programs, and the like. As shown in fig. 5, the computer device 01 of the present embodiment at least includes but is not limited to: a memory 011 and a processor 012, which are communicatively connected to each other via a system bus, as shown in fig. 5. It is noted that fig. 5 only shows the computer device 01 having the component memory 011 and the processor 012, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
In this embodiment, the memory 011 (i.e., a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage 011 can be an internal storage unit of the computer device 01, such as a hard disk or a memory of the computer device 01. In other embodiments, the memory 011 can also be an external storage device of the computer device 01, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer device 01. Of course, the memory 011 can also include both internal and external memory units of the computer device 01. In this embodiment, the memory 011 is generally used for storing an operating system installed in the computer device 01 and various application software, such as a program code of the face recognition apparatus of the second embodiment. Further, the memory 011 can also be used to temporarily store various kinds of data that have been output or are to be output.
The processor 012 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data Processing chip in some embodiments. The processor 012 is generally used to control the overall operation of the computer device 01. In this embodiment, the processor 012 is configured to run a program code stored in the memory 011 or process data, such as a face recognition method.
EXAMPLE five
The fifth embodiment further provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor implements corresponding functions. The computer-readable storage medium of this embodiment is used to store a face recognition device, and when executed by a processor, implements the face recognition method of the first embodiment.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A face recognition method, comprising:
reading a tag signal of an electronic tag carried by a target user, wherein the electronic tag is bound with the target user;
acquiring a face comparison characteristic corresponding to the label signal;
acquiring a face image of the target user;
matching the feature data of the face image of the target user with the face comparison feature;
and determining a face recognition result according to the matching result.
2. The face recognition method of claim 1, wherein the electronic tag is a UHF electronic tag disposed on a helmet.
3. The face recognition method according to claim 2, wherein the tag signal includes identification information of a safety helmet, and the step of obtaining the face comparison feature corresponding to the tag signal includes:
analyzing the label signal to obtain the identification information of the safety helmet;
and searching the face comparison characteristics corresponding to the identification information in a sample database.
4. The face recognition method of claim 3, further comprising:
receiving user personal information, wherein the user personal information comprises identification information of a safety helmet;
acquiring a face image of a user to obtain a plurality of face image samples;
calculating the face comparison characteristics according to the face image samples; and
and storing the identification information and the face comparison characteristics to the sample database.
5. The face recognition method of claim 4,
the step of obtaining the face comparison characteristics corresponding to the label signal further comprises the following steps of, after the step of analyzing the label signal to obtain the identification information of the safety helmet, and before the step of searching the face comparison characteristics corresponding to the identification information in a sample database: searching the face comparison times corresponding to the identification information in the sample database;
the step of searching the face comparison characteristics corresponding to the identification information in the sample database comprises the following steps: when the face comparison times meet a preset requirement, searching a face comparison characteristic corresponding to the identification information in a sample database;
the face recognition method further comprises the following steps: and when the face comparison times do not meet the preset requirement, outputting prompt information for identifying overrun.
6. The face recognition method of claim 5, further comprising:
and after searching the face comparison characteristics corresponding to the identification information in a sample database, subtracting 1 from the face comparison times corresponding to the identification information, wherein the initial value of the face comparison times is a face comparison time threshold.
7. A face recognition apparatus, comprising:
the reading module is used for reading a tag signal of an electronic tag carried by a target user, wherein the electronic tag is bound with the target user;
the acquisition module is used for acquiring the face comparison characteristics corresponding to the label signals;
the acquisition module is used for acquiring the face image of the target user;
the matching module is used for matching the feature data of the face image with the comparison feature;
and the determining module is used for determining a face recognition result according to the matching result.
8. A face recognition system, comprising: electronic tags, signal reading module, control module group and image acquisition module, wherein:
the electronic tag is used for generating a tag signal, wherein the electronic tag is bound with the target user;
the signal reading module is used for reading the label signal;
the image acquisition module is used for acquiring a face image of a target user;
the control module is used for acquiring a face comparison characteristic corresponding to the label signal, matching the characteristic data of the face image with the comparison characteristic, and determining a face recognition result according to a matching result.
9. A computer device 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 by the processor when executing the computer program.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program when executed by a processor implements the steps of the method of any one of claims 1 to 6.
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