CN110619689A - Automatic sign-in and card-punching method for smart building, computer equipment and storage medium - Google Patents
Automatic sign-in and card-punching method for smart building, computer equipment and storage medium Download PDFInfo
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- CN110619689A CN110619689A CN201910813987.1A CN201910813987A CN110619689A CN 110619689 A CN110619689 A CN 110619689A CN 201910813987 A CN201910813987 A CN 201910813987A CN 110619689 A CN110619689 A CN 110619689A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
- G06V40/23—Recognition of whole body movements, e.g. for sport training
- G06V40/25—Recognition of walking or running movements, e.g. gait recognition
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/10—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people together with the recording, indicating or registering of other data, e.g. of signs of identity
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Abstract
The invention discloses an automatic sign-in and card-punching method for intelligent buildings, computer equipment and a readable storage medium, wherein the method comprises the following steps: in a target time period, acquiring a current face picture and a historical face picture of a target employee, and then performing face feature matching processing on the current face picture and the historical face picture to obtain a face matching result whether matching passes or not; if so, determining that the target employee successfully signs and prints the attendance, so that attendance checking and printing are carried out in a non-contact mode, the attendance checking and printing speed is increased, and the attendance checking and printing efficiency is improved; if not, sending other biological characteristic acquisition instructions to the client, acquiring other biological characteristics of the target employee and historical biological characteristics, carrying out characteristic matching processing on the other biological characteristics and the historical biological characteristics to obtain a characteristic matching result of whether the matching is passed, and when the characteristic matching result is the matching pass, determining that the target employee successfully signs and checks the attendance, thereby ensuring the validity of the attendance checking and checking.
Description
Technical Field
The invention relates to the field of data processing, in particular to an automatic sign-in and card-punching method for smart buildings, computer equipment and a readable storage medium.
Background
With increasingly intense competition between enterprises, many enterprises adopt various methods to improve the output efficiency of the enterprises, and the method for fully exerting the value of each worker is a method for improving the output efficiency, so that the enterprises can strictly manage the attendance system of the workers.
In the traditional method, the attendance checking card punching mode is signature or IC card swiping, which usually shows the phenomenon of attendance checking by modern people, and the subsequent attendance checking modes such as fingerprint card punching appear, but in the smart building, when the work is on and off, because the number of workers to be checked is large, long-time queuing is needed to be spent for fingerprint check, so that the attendance checking card punching efficiency is low.
Therefore, finding an efficient attendance check-in and card-punching method becomes a problem that needs to be solved urgently by technical personnel in the field.
Disclosure of Invention
The embodiment of the invention provides an automatic attendance checking and card punching method for smart buildings, computer equipment and a readable storage medium, and aims to solve the problem of low attendance checking and card punching efficiency.
An automatic check-in and card-punching method for smart buildings comprises the following steps:
acquiring a current face picture of a target employee sent by a client in a preset target time period, and acquiring a historical face picture of the target employee, which is acquired in advance;
carrying out face feature matching processing on the current face picture and the historical face picture to obtain a face matching result whether matching is passed or not;
when the face matching result is matching pass, determining that the target employee signs and prints the card successfully;
when the face matching result is that the matching fails, sending other biological feature acquisition instructions to the client so that the client can perform other biological feature acquisition processing on the target employee based on the other biological feature acquisition instructions, wherein the other biological features are biological features except the face features of the target employee;
acquiring the other biological characteristics of the target employee, which are acquired through the other biological characteristic acquisition instruction and sent by the client, and acquiring historical biological characteristics of the target employee, which are acquired in advance;
performing feature matching processing on the other biological features and the historical biological features to obtain a feature matching result whether the matching is passed or not;
and when the characteristic matching result is that the matching is passed, determining that the target employee successfully signs and prints the card.
A computer device comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the automatic check-in and card-punching method of the intelligent building.
A computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the steps of the above-described method for automatic check-in and card-punching for smart buildings.
In the automatic sign-in and card-punching method, the computer equipment and the readable storage medium for the intelligent building, a current face picture of a target employee sent by a client and a historical face picture of the target employee collected in advance are obtained within a preset target time period, and then face feature matching processing is carried out on the current face picture and the historical face picture to obtain a face matching result whether matching passes or not; if so, determining that the target employee successfully signs and punches the card, so that attendance checking and punching are carried out in a non-contact mode, the speed of attendance checking and punching is increased, and the efficiency of attendance checking and punching is improved; when the face matching result is that the matching is not passed, sending other biological characteristic acquisition instructions to a client, then acquiring the other biological characteristics of the target employee sent by the client and acquiring the historical biological characteristics of the target employee which are acquired in advance, finally performing characteristic matching processing on the other biological characteristics and the historical biological characteristics to obtain a characteristic matching result whether the matching is passed or not, and when the characteristic matching result is that the matching is passed, determining that the target employee is signed in and printed with the card successfully, thereby ensuring the validity of the attendance check.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a diagram illustrating an application environment of an automatic check-in and card-punching method for intelligent buildings according to an embodiment of the present invention;
FIG. 2 is a flowchart of an automatic check-in and card-punching method for intelligent buildings according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating the analysis of employee images of a target employee and the identification of a target gait in an automatic check-in and check-out method for smart buildings according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating an example of obtaining and matching fingerprint strength and fingerprint area of a target employee in an automatic check-in and check-out method for a smart building according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present 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.
The automatic check-in and card-punching method for the intelligent building can be applied to an application environment shown in fig. 1, wherein the application environment comprises a server and a client, and the client communicates with the server through a wired network or a wireless network. Among other things, the client may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of a plurality of servers. The client is used for collecting the biological characteristics of the target employee, and the server is used for analyzing and identifying the biological characteristics of the target employee.
In an embodiment, as shown in fig. 2, an automatic check-in and card-punching method for smart buildings is provided, which is described by taking the method applied to the server in fig. 1 as an example, and includes the following steps:
s101, in a preset target time period, acquiring a current face picture of a target employee sent by a client, and acquiring a historical face picture of the target employee, wherein the historical face picture is acquired in advance.
Specifically, under a normal condition, a human face picture client is installed on a passage through which workers on each office floor of the intelligent building enter and exit an office, and the client acquires the current human face picture of each target worker in real time in a preset target time period. It is understood that the current face picture refers to a current face-included picture of the target employee.
For example, a face image acquisition device is installed at a front entrance of a 31-storey building of a Chinese space building, and the face image acquisition device acquires the current face image of each target employee before the working time of 8:30 in working days, namely, between 00:00 and 8: 30.
When each employee enters the job, the client acquires a historical face picture of the target employee in advance and stores the historical face picture into the face picture database, in order to analyze the matching degree of the current face picture of the target employee and the historical face picture, a storage path of the historical face picture needs to be acquired in the face picture database, and then the historical face picture is extracted according to the storage path. It is understood that the current face picture refers to a current face-included picture of the target employee.
For example, the face picture database is a MySQL database, the storage path of the historical face picture is "C: \ ProgramFiles \ MySQL \ MySQL Server5.0\ data \", firstly, the C: \ ProgramFiles \ MySQL \ MySQL Server5.0\ data \ is obtained in the MySQL database, and then the historical face picture is extracted according to the "C: \ ProgramFiles \ MySQL \ MySQLServer5.0\ data".
It should be noted that the acquisition device may be a camera or a digital camera, the face image database may be a MySQL database or an oracle database, and the specific contents of the acquisition device, the face image database, and the target time period may be set according to practical applications, which is not limited herein.
And S102, carrying out face feature matching processing on the current face picture and the historical face picture to obtain a face matching result whether the matching is passed or not.
Wherein, specifically include: firstly, inputting a current face picture into a pre-trained face feature extraction model to perform face feature extraction processing to obtain the current face feature of a target employee, namely, segmenting the current face picture to obtain a first region of the current face picture and a second region of the current face picture; the method comprises the steps of segmenting a first region of a current face picture to obtain a third region and a fourth region of the current face picture, and segmenting a second region of the current face picture to obtain a fifth region and a sixth region of the current face picture; and inputting the third area, the fourth area, the fifth area and the sixth area in the current face picture into a pre-trained face feature extraction model one by one to extract face features, so as to obtain the current face features of the target employee. Then inputting the historical face picture into a pre-trained face feature extraction model for face feature extraction processing to obtain the historical face feature of the target employee; judging whether the current face features are consistent with the historical face features; if the current face features are consistent with the historical face features, determining that the face matching result is a matching pass; and if the current face features are not consistent with the historical face features, determining that the face matching result is that the matching fails.
It is understood that the first region and the second region do not intersect each other, the third region and the fourth region do not intersect each other, and the fifth region and the sixth region do not intersect each other. The first region corresponds to a first type organ, the second region corresponds to a second type organ, the proportion of the area of the first region to the total area of the current face picture is greater than or equal to a preset threshold, and the proportion of the area of the second region to the total area of the current face picture is smaller than the preset threshold. The face area occupied by the first area is large, and the first area comprises: hair region or face region, the face area that the second region accounts for is less, and the second region includes: left eye and left eyebrow area, right eye and right eyebrow area, nose area, or mouth area. The third area and the fourth area are one part of the first area, and the fifth area and the sixth area are one part of the second area.
It should be noted that the face feature extraction model may be a convolutional neural network model, and may also be other models, and specific contents of the face feature extraction model may be set according to practical applications, which is not limited herein.
Through the step S102, the accurate segmentation and positioning of the first region with the large face area and the accurate segmentation and positioning of the second sub-region with the small face area are realized, compared with the related technology, in the face segmentation process, the number of network layers needed for better interaction is large, the required calculation time is long, and the problems of low face recognition accuracy and long occupied calculation time in the prior art are solved, so that the complexity required by a sub-network is reduced, the calculation time required by face segmentation is reduced, and the accuracy and the efficiency of face recognition are improved.
S103, when the face matching result is that the match is passed, the target employee is determined to be successfully signed and checked.
Specifically, when the face matching result in step S102 is that the match is passed, it is determined that the target employee successfully checked the card, that is, if the face of the current picture is the face of the target employee, it is determined that the target employee has arrived at the office, so as to determine that the target employee successfully checked the card.
And S104, when the face matching result is that the matching is not passed, sending other biological feature acquisition instructions to the client so that the client can perform other biological feature acquisition processing on the target employee based on the other biological feature acquisition instructions, wherein the other biological features are biological features except the face features of the target employee.
Specifically, when the face matching result is that the matching fails, the server sends the other biological feature acquisition instructions to the client, and when the client receives the other biological feature acquisition instructions, the client performs other biological feature acquisition processing on the target employee according to the other biological feature acquisition instructions to obtain other biological features of the target employee, and sends the acquired other biological features to the server.
The other biological characteristics are biological characteristics except the human face characteristics of the target employee, the biological characteristics comprise physiological characteristics and behavior characteristics, the physiological characteristics comprise fingerprints, irises, facies, DNA and the like, and the behavior characteristics comprise gait, keystroke habits and the like.
And S105, acquiring other biological characteristics of the target employee, which are acquired through other biological characteristic acquisition instructions and sent by the client, and acquiring historical biological characteristics of the target employee, which are acquired in advance.
Specifically, in order to analyze and compare the biological characteristics of the target employee, the other biological characteristics of the target employee, which are acquired through other biological characteristic acquisition instructions sent by the client, are firstly acquired, then a storage path of the historical biological characteristics of the target employee, which are acquired in advance, is acquired in the characteristic database, and then the historical biological characteristics are acquired according to the storage path.
It should be noted that the feature database may be a MySQL database or an oracle database, and the specific content of the feature database may be set according to the practical application, which is not limited herein.
And S106, performing feature matching processing on other biological features and historical biological features to obtain a feature matching result whether the matching is passed or not.
When other biological characteristics are target fingerprints, the other biological characteristics and historical biological characteristics are subjected to characteristic matching processing to obtain a characteristic matching result which indicates whether the matching is passed, and the method specifically comprises the following steps: carrying out texture extraction processing on the target fingerprint to obtain the current fingerprint texture of the target employee; acquiring pre-collected historical fingerprint lines of a target employee; judging whether the current fingerprint lines are consistent with the historical fingerprint lines; if the current fingerprint lines are consistent with the historical fingerprint lines, determining that the feature matching result is that the matching is passed; and if the current fingerprint texture is not consistent with the historical fingerprint texture, determining that the characteristic matching result is that the matching is failed.
Further, after the characteristic matching result is determined to be that the matching fails, the target employee is determined to fail to sign in and check in, and meanwhile prompt information of the failure of signing in and checking in is output.
And S107, when the feature matching result is that the matching is passed, determining that the target employee successfully checks the card.
Specifically, when the feature matching result in step S106 is that the matching is passed, it is determined that the target employee successfully checked the card, that is, if the target fingerprint is the fingerprint of the target employee, it is determined that the target employee has arrived at the office location, so as to determine that the target employee successfully checked the card; when the feature matching result in step S106 is that the matching fails, it is determined that the target employee failed to check in, that is, if the target fingerprint is not the fingerprint of the target employee, it is determined that the target employee has not arrived at the office location, so as to determine that the target employee failed to check in.
In the embodiment corresponding to fig. 2, a current face picture of a target employee sent from a client and a historical face picture of the target employee collected in advance are obtained first within a preset target time period, and then face feature matching processing is performed on the current face picture and the historical face picture to obtain a face matching result whether matching is passed or not; if so, determining that the target employee successfully signs and punches the card, so that attendance checking and punching are carried out in a non-contact mode, the speed of attendance checking and punching is increased, and the efficiency of attendance checking and punching is improved; and when the face matching result is that the matching is not passed, sending other biological characteristic acquisition instructions to a client, then acquiring the other biological characteristics of the target employee sent by the client and acquiring the historical biological characteristics of the target employee acquired in advance, finally performing characteristic matching processing on the other biological characteristics and the historical biological characteristics to obtain a characteristic matching result of whether the matching is passed, and when the characteristic matching result is that the matching is passed, determining that the target employee successfully signs and prints the card, thereby ensuring the validity of checking-in, signing and printing the card.
In a specific embodiment, as shown in fig. 3, in step S101, that is, in a preset target time period, obtaining a current face picture of a target employee sent from a client, and before obtaining a historical face picture of the target employee collected in advance, analyzing the employee picture of the target employee and recognizing a target gait specifically includes the following steps:
s201, in a target time period, acquiring a staff image of a target staff.
Specifically, the client acquires the employee pictures of each target employee who enters and exits the office location in a target time period, and sends the employee pictures to the server through a wired or wireless network, and the server receives the employee pictures in real time.
It should be noted that the content of the target time period in step S201 is identical to the content of the target time period in step S101, and will not be described here.
S202, judging whether the employee picture is a face picture.
Specifically, the employee picture acquired in step S202 is input into a preset picture recognition model, an output result indicating whether the employee picture includes a face is obtained, when the output result indicates that the employee picture includes a face, the employee picture is determined to be a face picture, and when the output result indicates that the employee picture does not include a face, the employee picture is determined not to be a face picture.
It should be noted that the image recognition model may be a neural network model, and may also be other models, and specific contents of the image recognition model may be set according to practical applications, which is not limited herein.
And S203, when the employee picture is the face picture, executing the steps of acquiring the current face picture of the target employee sent by the client in a preset target time period and acquiring the historical face picture of the target employee collected in advance.
Specifically, when the employee image is a face image, step S101 is executed, that is, when the face information of the target employee is acquired, the face information may be acquired, and analyzed and compared.
And S204, when the picture of the employee is not the face picture, acquiring the target gait of the target employee sent by the client.
Specifically, when the image of the employee is not a face image, that is, when the face information of the target employee is not collected, the server side acquires the target gait of the target employee sent by the client side, so as to compare and analyze the target gait with the historical gait, and thus identify the identity information of the target employee.
And S205, acquiring the pre-collected historical gait of the target employee.
Specifically, in order to analyze and compare whether the target gait is the gait of the target employee, a pre-collected storage path of the historical gait of the target employee needs to be acquired in the gait database, and then the historical gait is extracted according to the storage path.
It should be noted that the gait database may be a MySQL database or an oracle database, and the specific content of the gait database may be set according to the practical application, which is not limited herein.
Further, before S205, the method further includes: preprocessing a staff picture to obtain a target picture to be identified; the method comprises the steps of performing gait recognition processing on a target picture by adopting a preset gait recognition algorithm to obtain a target gait of a target worker, namely performing motion detection and motion segmentation on the target worker, and finally performing gait recognition, wherein the gait recognition algorithm can be a GaitSet algorithm or other algorithms, the specific content of the gait recognition algorithm can be set according to practical application, and the specific content is not limited here.
And S206, carrying out gait matching processing on the target gait and the historical gait to obtain a gait matching result whether the matching is passed or not.
Specifically, gait matching processing is carried out on the target gait and the historical gait to obtain a gait matching result whether the matching is passed or not, namely, whether the target gait is consistent with the historical gait or not is judged, when the target gait is consistent with the historical gait, the gait matching result is determined to be passed, and when the target gait is not consistent with the historical gait, the gait matching result is determined to be failed in matching.
And S207, when the gait matching result is that the match is passed, determining that the target employee signs and checks the card successfully.
Specifically, when the gait matching result is that the matching is passed, the target employee is represented to have arrived at the office, and therefore the target employee is determined to have successfully signed and checked the card; and when the gait matching result is that the matching is not passed, the target employee is represented to have not arrived at the office, so that the target employee is determined to have failed to sign in and check in the card.
In the embodiment corresponding to fig. 3, through the steps S201 to S207, different recognition schemes can be flexibly executed according to whether the face information of the target employee is collected, so that the accuracy of identity recognition of the target employee is improved.
In an embodiment, as shown in fig. 4, before determining that the feature matching result is a match pass, the method further includes obtaining and matching the fingerprint strength and the fingerprint area of the target employee, and specifically includes the following steps:
s301, acquiring the fingerprint strength and the fingerprint area of a target employee sent by the client when the target employee presses the fingerprint currently.
Specifically, the client side collects the fingerprint strength and the fingerprint area of the target employee when the fingerprint is pressed at present while collecting the target fingerprint of the target employee, and sends the collected fingerprint strength and the collected fingerprint area to the server side, and the server side receives the fingerprint strength and the fingerprint area in real time.
Wherein, the fingerprint dynamics is the dynamics of target worker when pressing the fingerprint at present, and the fingerprint area is the area of target worker when pressing the fingerprint at present.
S302, acquiring the historical strength and the historical area of the target employee during historical fingerprint pressing, wherein the historical strength and the historical area are acquired in advance.
Specifically, in order to analyze and compare the strength and the area of the target employee when the fingerprint is pressed, a pre-collected storage path of the historical strength and the historical area of the target employee when the fingerprint is pressed historically needs to be obtained from the historical database, and the historical strength and the historical area are extracted according to the storage path.
And S303, when the fingerprint strength is consistent with the historical strength and the fingerprint area is consistent with the historical area, executing a step of determining that the characteristic matching result is a matching pass.
Specifically, when the fingerprint strength acquired in step S301 is consistent with the history strength acquired in step S302, and the fingerprint area acquired in step S301 is consistent with the history area acquired in step S302, it is determined that the target employee reaches the office location for oneself, and meanwhile, it is determined that the feature matching result is a match pass; when the fingerprint strength acquired in step S301 is not consistent with the history strength acquired in step S302, and/or the fingerprint area acquired in step S301 is not consistent with the history area acquired in step S302, it is determined that the target employee is a person who has not reached the office location, and the feature matching result is determined as a matching failure.
In the embodiment corresponding to fig. 4, through the steps S301 to S303, when the fingerprint of the target employee is matched and the fingerprint strength and the fingerprint area of the target employee when the fingerprint is currently pressed are also matched, the target employee is considered to be the principal, so that the identification accuracy of the identity is improved.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile readable storage medium, an internal memory. The non-transitory readable 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 readable storage medium. The database of the computer device is used for storing data related to an automatic check-in and card-punching method of the intelligent building. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to realize an automatic check-in and card-punching method for the intelligent building.
In one embodiment, a computer device is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the automatic check-in and card-punching method for smart buildings according to the above embodiments are implemented, for example, steps S101 to S107 shown in fig. 2.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, the computer program, when executed by a processor, implementing the automatic check-in and card-punching method for smart buildings in the above method embodiments. 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 hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An automatic check-in and card-punching method for smart buildings is characterized by comprising the following steps:
acquiring a current face picture of a target employee sent by a client in a preset target time period, and acquiring a historical face picture of the target employee, which is acquired in advance;
carrying out face feature matching processing on the current face picture and the historical face picture to obtain a face matching result whether matching is passed or not;
when the face matching result is matching pass, determining that the target employee signs and prints the card successfully;
when the face matching result is that the matching fails, sending other biological feature acquisition instructions to the client so that the client can perform other biological feature acquisition processing on the target employee based on the other biological feature acquisition instructions, wherein the other biological features are biological features except the face features of the target employee;
acquiring the other biological characteristics of the target employee, which are acquired through the other biological characteristic acquisition instruction and sent by the client, and acquiring historical biological characteristics of the target employee, which are acquired in advance;
performing feature matching processing on the other biological features and the historical biological features to obtain a feature matching result whether the matching is passed or not;
and when the characteristic matching result is that the matching is passed, determining that the target employee successfully signs and prints the card.
2. The method as claimed in claim 1, wherein before acquiring the current face picture of the target employee from the client and acquiring the pre-collected historical face picture of the target employee within the preset target time period, the method further comprises:
acquiring a staff picture of the target staff within the target time period;
judging whether the employee picture is a face picture;
when the employee picture is the face picture, executing the step of acquiring the current face picture of the target employee sent by the client within a preset target time period and acquiring the historical face picture of the target employee which is acquired in advance;
when the employee picture is not the face picture, acquiring a target gait of the target employee sent by the client;
acquiring the pre-collected historical gait of the target employee;
carrying out gait matching processing on the target gait and the historical gait to obtain a gait matching result whether the matching is passed or not;
and when the gait matching result is that the matching is passed, determining that the target employee signs and checks the card successfully.
3. The method of claim 2, wherein prior to the obtaining of the target gait of the target employee from the client, the method further comprises:
preprocessing the employee picture to obtain a target picture to be identified;
and adopting a preset gait recognition algorithm to perform gait recognition processing on the target picture to obtain the target gait of the target employee.
4. The automatic check-in and card-punching method for intelligent buildings according to any one of claims 1 to 3, wherein the step of performing face feature matching processing on the current face picture and the historical face picture to obtain a face matching result whether matching is passed or not comprises the following steps:
inputting the current face picture into a pre-trained face feature extraction model for face feature extraction processing to obtain the current face feature of the target employee;
inputting the historical face picture into a pre-trained face feature extraction model for face feature extraction processing to obtain the historical face feature of the target employee;
judging whether the current face features are consistent with the historical face features;
if the current face features are consistent with the historical face features, determining that the face matching result is a matching pass;
and if the current face features are not consistent with the historical face features, determining that the face matching result is a matching failure.
5. The method as claimed in claim 4, wherein the step of inputting the current face picture into a pre-trained face feature extraction model for face feature extraction processing to obtain the current face feature of the target employee comprises:
segmenting the current face picture to obtain a first region of the current face picture and a second region of the current face picture;
segmenting a first region of the current face picture to obtain a third region and a fourth region of the current face picture, and segmenting a second region of the current face picture to obtain a fifth region and a sixth region of the current face picture, wherein the first region and the second region are not intersected with each other, the third region and the fourth region are not intersected with each other, and the fifth region and the sixth region are not intersected with each other;
inputting the third area, the fourth area, the fifth area and the sixth area in the current face picture into a pre-trained face feature extraction model one by one for face feature extraction processing, so as to obtain the current face features of the target employee.
6. The method as claimed in claim 1, wherein the other biometric features are target fingerprints, and the matching of the other biometric features with the historical biometric features to obtain a matching result comprises:
performing texture extraction processing on the target fingerprint to obtain the current fingerprint texture of the target employee;
acquiring pre-collected historical fingerprint lines of the target employee;
judging whether the current fingerprint lines are consistent with the historical fingerprint lines;
if the current fingerprint texture is consistent with the historical fingerprint texture, determining that the feature matching result is a matching pass;
and if the current fingerprint texture is not consistent with the historical fingerprint texture, determining that the feature matching result is that the matching is failed.
7. The method as claimed in claim 6, wherein the method for automatically checking in and checking out the smart building comprises, before the determining that the feature matching result is a match, the steps of:
acquiring the fingerprint strength and the fingerprint area of the target employee sent by the client when the target employee presses the fingerprint currently;
acquiring the historical strength and the historical area of the target employee during historical fingerprint pressing, which are acquired in advance;
and when the fingerprint strength is consistent with the historical strength and the fingerprint area is consistent with the historical area, executing the step of determining that the characteristic matching result is a matching pass.
8. The automatic check-in and card-punching method for the intelligent building as claimed in claim 6 or 7, wherein after the determination that the feature matching result is a match failure, the automatic check-in and card-punching method for the intelligent building comprises:
and determining that the target employee fails to sign in and check out, and simultaneously outputting prompt information of the failure of signing in and checking out.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements the method for automatic check-in and card-punching for smart buildings according to any one of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method for automatic check-in and card-punching for smart buildings according to any one of claims 1 to 8.
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Application publication date: 20191227 |