CN111354096A - Intelligent attendance checking method and device and electronic equipment - Google Patents
Intelligent attendance checking method and device and electronic equipment Download PDFInfo
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- CN111354096A CN111354096A CN201910765173.5A CN201910765173A CN111354096A CN 111354096 A CN111354096 A CN 111354096A CN 201910765173 A CN201910765173 A CN 201910765173A CN 111354096 A CN111354096 A CN 111354096A
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- 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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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The invention discloses an intelligent attendance checking method and device and electronic equipment, wherein the intelligent attendance checking method comprises the following steps: acquiring image information including a plurality of detection objects; carrying out face recognition processing on the image information, and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects; and comparing the faces in the grids corresponding to the two graphs according to the grid position graph and the predetermined grid seat graph, and judging the matching degree of the detection objects in the corresponding grids to obtain an attendance result. The invention can simultaneously detect the attendance states of a plurality of detection objects and improve the attendance efficiency.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an intelligent attendance checking method and device and electronic equipment.
Background
The prior class attendance method generally refers to that a teacher calls a roll before class or students check in by using student cards, the efficiency of the calling method is low, the class time is wasted, the calling and checking-in method has the possibility of replacing the calling condition and can not truly reflect the attendance condition, and in the actual condition, the students escape from class after calling or checking in, and actually do not attend.
Disclosure of Invention
In view of the above, the present invention provides an intelligent attendance checking method, an intelligent attendance checking device, and an electronic device, which can simultaneously detect attendance checking states of a plurality of detection objects, and improve attendance checking efficiency and accuracy.
Based on the above purpose, the invention provides an intelligent attendance checking method, which comprises the following steps:
acquiring image information including a plurality of detection objects;
carrying out face recognition processing on the image information, and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects;
and comparing the faces in the grids corresponding to the two graphs according to the grid position graph and the predetermined grid seat graph, and judging the matching degree of the detection objects in the corresponding grids to obtain an attendance result.
Optionally, the method for processing the image information to generate the grid-shaped position map includes: and carrying out recognition processing on the image information, determining the positions of all human faces in the image information, and cutting the image information into the latticed position graph comprising a plurality of grids according to the positions of the human faces, wherein each grid comprises a group of human face information.
Optionally, the latticed seating map is obtained by dividing according to the seat position of each detection object, and each grid in the latticed seating map includes a face sample and basic information corresponding to the seat position;
and comparing the face information in each grid in the grid position diagram with the face samples in the corresponding grid in the grid seat diagram, and judging the attendance state of the detection object corresponding to each grid according to the comparison result.
Optionally, if the similarity between the face information in the grid-shaped position map and the face sample in the corresponding grid in the grid-shaped seat map is greater than a preset matching degree, it is determined that the corresponding detection object in the grid is on duty, and the identity information of the face information is determined according to the basic information corresponding to the face sample; and if the similarity is smaller than the matching degree or no face information exists in the grid-shaped position diagram, judging that the corresponding detection object in the grid is absent.
Optionally, within a predetermined time period, the attendance result is continuously obtained, a predetermined attendance result is obtained through statistics, and the predetermined attendance result is sent to the terminal and displayed on the terminal.
Optionally, within a predetermined time period, the attendance result is continuously obtained, the attendance time of each detection object within the predetermined time period is counted, and if the attendance time of a specific detection object is greater than a preset attendance time threshold, it is determined that the specific detection object is absent.
The embodiment of the invention provides an intelligent attendance checking device, which comprises:
an image acquisition unit configured to acquire image information including a plurality of detection objects;
the image recognition module is used for carrying out face recognition processing on the image information and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects;
and the attendance checking detection module is used for comparing the faces in the grids corresponding to the two graphs according to the latticed position graph and the predetermined latticed seat graph, judging the matching degree of the detection objects in the corresponding grids and obtaining an attendance checking result.
Optionally, the image recognition module includes:
the face recognition submodule is used for carrying out recognition processing on the image information and determining the positions of all faces in the image information;
and the position map generation submodule is used for cutting the image information into a grid-shaped position map comprising a plurality of grids according to the positions of all the human faces, and each grid comprises a group of human face information.
Optionally, the latticed seating map is obtained by dividing according to the seat position of each detection object, and each grid in the latticed seating map includes a face sample and basic information corresponding to the seat position;
the attendance checking detection module compares the face information in each grid in the latticed position diagram with the face samples in the corresponding grid in the latticed seat diagram, and judges the attendance state of the detection object corresponding to each grid according to the comparison result.
Optionally, if the similarity between the face information in the grid-shaped position map and the face sample in the corresponding grid in the grid-shaped seat map is greater than a preset matching degree, it is determined that the corresponding detection object in the grid is on duty, and the identity information of the face information is determined according to the basic information corresponding to the face sample; and if the similarity is smaller than the matching degree or no face information exists in the grid-shaped position diagram, judging that the corresponding detection object in the grid is absent.
Optionally, the apparatus further comprises:
the statistical module is used for continuously obtaining the attendance checking result within a preset time period, and performing statistics to obtain a preset attendance checking result;
and the data sending module is used for sending the preset attendance checking result to a terminal and displaying the preset attendance checking result on the terminal.
Optionally, the apparatus further comprises:
and the attendance counting module is used for continuously obtaining the attendance result within a preset time period, counting the attendance absence time of each detection object within the preset time period, and judging that the specific detection object is absent if the attendance absence time of the specific detection object is greater than a preset attendance absence time threshold value.
The embodiment of the invention also provides electronic equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the intelligent attendance checking method.
From the above, the intelligent attendance method, the intelligent attendance device and the electronic equipment provided by the invention acquire the image information comprising a plurality of detection objects, perform face recognition processing on the image information, process the image information according to the face positions of the recognized detection objects to generate the grid-shaped position map, compare the faces in the grids corresponding to the two maps according to the grid-shaped position map and the predetermined grid-shaped seat map, and judge the matching degree of the detection objects in the corresponding grids to obtain the attendance result. The invention can simultaneously detect the attendance states of a plurality of detection objects and improve the attendance efficiency; the attendance accuracy can be improved by counting the attendance result within a certain time period as a final attendance result.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method according to an embodiment of the present invention;
fig. 2 is a block diagram of an apparatus according to an 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 specific embodiments and the accompanying drawings.
It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are used for distinguishing two entities with the same name but different names or different parameters, and it should be noted that "first" and "second" are merely for convenience of description and should not be construed as limitations of the embodiments of the present invention, and they are not described in any more detail in the following embodiments.
FIG. 1 is a schematic flow chart of a method according to an embodiment of the present invention. As shown in the figure, the intelligent attendance method provided by the embodiment of the invention comprises the following steps:
s10: acquiring image information including a plurality of detection objects;
in some embodiments, video information including the detection object is acquired by using an image acquisition device, and a video frame image is extracted from the video information as image information according to a preset time for subsequent identification processing. For example, in the attendance checking time period before class, extracting image information from the video information every 1.5 seconds; during the period of the in-class attendance, one image information is extracted from the video information every 30 seconds.
An image acquisition device can be installed in the specific area and used for acquiring image information of all detection objects in the specific area. For example, in a class attendance scene, a camera is installed in front of a classroom and used for acquiring image information of all students in the classroom.
S11: carrying out face recognition processing on the image information, and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects;
in some embodiments, the image information is subjected to recognition processing, the positions of all faces in the image information are recognized, and the image information is cut into a grid-shaped position map comprising a plurality of grids according to the positions of all the faces, wherein each grid comprises a group of face information. Specifically, the method comprises the steps of identifying position areas of all human faces in image information, determining a grid division range of the human face by taking the position area of the human face as a reference for the position area of each human face, dividing a grid corresponding to the human face according to the grid division range, and then identifying the human face in the grid to obtain human face information corresponding to the grid, wherein the human face information comprises face characteristic information, eye characteristic information, nose characteristic information, mouth characteristic information, eyebrow characteristic information and other human face identification characteristic information. According to the method, the image information is processed into a grid-shaped position graph comprising a plurality of grids, each grid comprises a group of face information, if there are absent students, empty grids exist in the image information after the grids are divided, and no face information exists in the empty grids. For the generated grid-shaped position diagram, numbers are sequentially distributed to each grid, and the grid-shaped position diagram with the numbers is obtained.
S12: and comparing the faces in the grids corresponding to the two graphs according to the grid position graph and the predetermined grid seat graph, and judging the matching degree of the detection objects in the corresponding grids to obtain an attendance result.
In the application scene of school, because the number of students in each classroom is fixed and the seats of students are fixed, the seat map including all students can be determined in advance by the following method: for a specific class, inputting face samples and basic information of all students, enabling the face samples and the basic information of each student to correspond to the seat positions of the students, and generating a grid-shaped seat map divided according to the seat positions of the students, wherein each grid in the seat map comprises the face samples and the basic information (information such as name, gender, school number, class, school and the like) of the students at the seat positions. And allocating numbers to each grid in the seat table in sequence to obtain a numbered seat table, wherein the grid numbering mode of the seat table is the same as that of the position table.
When the attendance check before class is carried out within the preset time period before class, acquiring the image information of all students in a classroom in real time according to the step S10, and carrying out face recognition processing on the image information according to the step S11 to generate a grid-shaped position diagram; and comparing the face in the corresponding grid in the position map and the seat map according to the position map and the predetermined seat map, and judging the attendance state of the student corresponding to the grid according to the comparison result. Taking one of the grids as an example, comparing and identifying the face information of the first grid in the position map with the face sample of the first grid in the seat map, judging the similarity of the two grids, if the similarity of the two grids is greater than a preset matching degree, judging that the students at the seat position corresponding to the first grid in the seat map normally attendance, and determining the identity information of the face information according to the basic information corresponding to the face sample, namely determining the identity information of the students in the first grid; and if the similarity of the two is smaller than the preset matching degree or the first grid in the position map is an empty grid, judging that the students in the seat positions corresponding to the first grid in the seat map do not work. According to the process, the attendance state of the students at the seat positions corresponding to each grid in the seat diagram is sequentially judged, and finally the attendance result before class is obtained.
Checking attendance in class within class time, continuously performing the steps S10-S12 to obtain the result of checking attendance in class, regularly summarizing the result of checking attendance in class, counting the in-class absent time of each student, setting an absent time threshold, and judging that a student is absent if the in-class absent time of a certain student is greater than the absent time threshold.
In some embodiments, the intelligent attendance method further comprises:
s13: and sending the obtained attendance result to the terminal, and displaying the attendance result on the terminal.
In some embodiments, the class attendance result can be sent and displayed on an electronic whiteboard in a classroom, or sent and displayed on a mobile terminal of a teacher, so that the teacher can visually check the class attendance result conveniently; can send the in-class result of examining the attendance of statistics to teacher's mobile terminal or management terminal, the later stage of being convenient for is according to statistical data and is carried out teaching management.
Fig. 2 is a block diagram of an apparatus according to an embodiment of the present invention. As shown in the figure, the intelligent attendance device provided by the embodiment of the invention comprises:
an image acquisition unit configured to acquire image information including a plurality of detection objects;
the image recognition module is used for carrying out face recognition processing on the image information and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects;
and the attendance checking detection module is used for comparing the faces in the grids corresponding to the two graphs according to the grid position graph and the predetermined grid seat graph, judging the matching degree of the detection objects in the corresponding grids and obtaining an attendance checking result.
In some embodiments, video information including the detection object is acquired by using an image acquisition device, and a video frame image is extracted from the video information as image information according to a preset time for subsequent identification processing. For example, in the attendance checking time period before class, extracting image information from the video information every 1.5 seconds; during the period of the in-class attendance, one image information is extracted from the video information every 30 seconds.
An image acquisition device can be installed in the specific area and used for acquiring image information of all detection objects in the specific area. For example, in a class attendance scene, a camera is installed in front of a classroom and used for acquiring image information of all students in the classroom.
In some embodiments, the image recognition module comprises:
the face recognition submodule is used for carrying out recognition processing on the image information and recognizing all face positions in the image information;
and the position map generation submodule is used for cutting the image information into a grid-shaped position map comprising a plurality of grids according to the positions of all the human faces, and each grid comprises a group of human face information.
In some embodiments, the position areas of all the faces in the image information are identified, for the position area of each face, the mesh division range of the face is determined based on the position area of the face, the mesh corresponding to the face is divided according to the mesh division range, and then the face in the mesh is identified to obtain the face information corresponding to the mesh, wherein the face information includes face identification feature information such as face features, eye features, nose features, mouth features, eyebrow features, and the like. According to the method, the image information is processed into a grid-shaped position graph comprising a plurality of grids, each grid comprises a group of face information, if there are absent students, empty grids exist in the image information after the grids are divided, and no face information exists in the empty grids. For the generated grid-shaped position diagram, numbers are sequentially distributed to each grid, and the grid-shaped position diagram with the numbers is obtained.
In the application scene of school, because the number of students in each classroom is fixed and the seats of students are fixed, the seat map including all students can be determined in advance by the following method: for a specific class, inputting face samples and basic information of all students, enabling the face samples and the basic information of each student to correspond to the seat positions of the students, and generating a grid-shaped seat map divided according to the seat positions of the students, wherein each grid in the seat map comprises the face samples and the basic information (information such as name, gender, school number, class, school and the like) of the students at the seat positions. And allocating numbers to each grid in the seat table in sequence to obtain a numbered seat table, wherein the grid numbering mode of the seat table is the same as that of the position table.
When the attendance check is carried out in the pre-class time period, the image acquisition unit is used for acquiring the image information of all students in a classroom in real time, and the image identification module is used for carrying out face identification processing on the image information to generate a grid-shaped position diagram; the attendance checking detection module compares the face in the corresponding grid in the position map and the seat map according to the position map and the predetermined seat map, and judges the attendance state of the student corresponding to the grid according to the comparison result. Taking one of the grids as an example, comparing and identifying the face information of the first grid in the position map with the face sample of the first grid in the seat map, judging the similarity of the two grids, if the similarity of the two grids is greater than a preset matching degree, judging that the students at the seat position corresponding to the first grid in the seat map normally attendance, and determining the identity information of the face information according to the basic information corresponding to the face sample, namely determining the identity information of the students in the first grid; and if the similarity of the two is smaller than the preset matching degree or the first grid in the position map is an empty grid, judging that the students in the seat positions corresponding to the first grid in the seat map do not work. According to the process, the attendance state of the students at the seat positions corresponding to each grid in the seat diagram is sequentially judged, and finally the attendance result before class is obtained.
In some embodiments, the intelligent attendance device further comprises:
and the attendance counting module is used for continuously obtaining attendance results within a preset time period, counting the attendance absence time of each detection object within preset time, and judging that the specific detection object is absent if the attendance absence time of the specific detection object is greater than a preset attendance absence time threshold value. For example, in class attendance is carried out within the class time, the attendance is continuously carried out by using the intelligent attendance device, the in class attendance result is obtained, in class attendance results are regularly collected, in class attendance time of each student is counted, an attendance time threshold value is set, and if in class attendance time of a certain student is greater than the attendance time threshold value, the student attendance is judged.
In some embodiments, the intelligent attendance device further comprises:
the statistical module is used for continuously obtaining the attendance checking result within a preset time period, and performing statistics to obtain a preset attendance checking result; optionally, the predetermined time period may be a first predetermined time period before class, and the predetermined attendance result is a class attendance result; or, the preset time period may be a class time period, and the preset attendance result is a class attendance result.
And the data sending module is used for sending the preset attendance checking result to the terminal and displaying the preset attendance checking result on the terminal.
In some embodiments, the class attendance result can be sent and displayed on an electronic whiteboard in a classroom, or sent and displayed on a mobile terminal of a teacher, so that the teacher can visually check the class attendance result conveniently; can send the in-class result of examining the attendance of statistics to teacher's mobile terminal or management terminal, the later stage of being convenient for is according to statistical data and is carried out teaching management.
Based on the above purpose, the embodiment of the present invention further provides an embodiment of an apparatus for executing the intelligent attendance method. The device comprises:
one or more processors, and a memory.
The apparatus for executing the intelligent attendance method may further include: an input device and an output device.
The processor, memory, input device, and output device may be connected by a bus or other means.
The memory, which is a non-volatile computer-readable storage medium, may be used to store a non-volatile software program, a non-volatile computer-executable program, and modules, such as program instructions/modules corresponding to the intelligent attendance method in the embodiments of the present invention. The processor executes various functional applications and data processing of the server by running the nonvolatile software program, instructions and modules stored in the memory, namely, the intelligent attendance method of the embodiment of the method is realized.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of an apparatus performing the smart attendance method, and the like. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory optionally includes memory remotely located from the processor, and these remote memories may be connected to the member user behavior monitoring device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device may receive input numeric or character information and generate key signal inputs related to user settings and function control of the device performing the intelligent attendance method. The output device may include a display device such as a display screen.
The one or more modules are stored in the memory and when executed by the one or more processors, perform the intelligent attendance method of any of the above method embodiments. The technical effect of the embodiment of the device for executing the intelligent attendance checking method is the same as or similar to that of any method embodiment.
The embodiment of the invention also provides a non-transitory computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the processing method of the list item operation in any method embodiment. Embodiments of the non-transitory computer storage medium may be the same or similar in technical effect to any of the method embodiments described above.
Finally, it should be noted that, as will be understood by those skilled in the art, all or part of the processes in the methods of the above embodiments may be implemented by a computer program that can be stored in a computer-readable storage medium and that, when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like. The technical effect of the embodiment of the computer program is the same as or similar to that of any of the method embodiments described above.
Furthermore, the apparatuses, devices, etc. described in the present disclosure may be various electronic terminal devices, such as a mobile phone, a Personal Digital Assistant (PDA), a tablet computer (PAD), a smart television, etc., and may also be large terminal devices, such as a server, etc., and therefore the scope of protection of the present disclosure should not be limited to a specific type of apparatus, device. The client disclosed by the present disclosure may be applied to any one of the above electronic terminal devices in the form of electronic hardware, computer software, or a combination of both.
Furthermore, the method according to the present disclosure may also be implemented as a computer program executed by a CPU, which may be stored in a computer-readable storage medium. The computer program, when executed by the CPU, performs the above-described functions defined in the method of the present disclosure.
Further, the above method steps and system elements may also be implemented using a controller and a computer readable storage medium for storing a computer program for causing the controller to implement the functions of the above steps or elements.
Further, it should be appreciated that the computer-readable storage media (e.g., memory) described herein can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. By way of example, and not limitation, nonvolatile 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), which can act as external cache memory. By way of example and not limitation, RAM is available in a variety of forms such as synchronous RAM (DRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The storage devices of the disclosed aspects are intended to comprise, without being limited to, these and other suitable types of memory.
The apparatus of the foregoing embodiment is used to implement the corresponding method in the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the invention, also features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
In addition, well known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown within the provided figures for simplicity of illustration and discussion, and so as not to obscure the invention. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the invention, and also in view of the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the present invention is to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the invention, it should be apparent to one skilled in the art that the invention can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements and the like that may be made without departing from the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (13)
1. An intelligent attendance checking method is characterized by comprising the following steps:
acquiring image information including a plurality of detection objects;
carrying out face recognition processing on the image information, and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects;
and comparing the faces in the grids corresponding to the two graphs according to the grid position graph and the predetermined grid seat graph, and judging the matching degree of the detection objects in the corresponding grids to obtain an attendance result.
2. The method of claim 1, wherein the processing the image information to generate the grid-like location map is by: and carrying out recognition processing on the image information, determining the positions of all human faces in the image information, and cutting the image information into the latticed position graph comprising a plurality of grids according to the positions of the human faces, wherein each grid comprises a group of human face information.
3. The method of claim 2,
dividing according to the seat position of each detection object to obtain the grid-shaped seat map, wherein each grid in the grid-shaped seat map comprises a face sample and basic information corresponding to the seat position;
and comparing the face information in each grid in the grid position diagram with the face samples in the corresponding grid in the grid seat diagram, and judging the attendance state of the detection object corresponding to each grid according to the comparison result.
4. The method according to claim 3, wherein if the similarity between the face information in the grid-shaped position map and the face sample in the corresponding grid in the grid-shaped seating map is greater than a preset matching degree, it is determined that the corresponding detection object in the grid is on duty, and the identity information of the face information is determined according to the basic information corresponding to the face sample; and if the similarity is smaller than the matching degree or no face information exists in the grid-shaped position diagram, judging that the corresponding detection object in the grid is absent.
5. The method of claim 1, wherein the attendance result is continuously obtained within a predetermined time period, a predetermined attendance result is obtained through statistics, and the predetermined attendance result is sent to a terminal and displayed on the terminal.
6. The method of claim 1, wherein the attendance result is continuously obtained within a predetermined time period, the absence time of each detection object within the predetermined time is counted, and if the absence time of a specific detection object is greater than a preset absence time threshold, absence of attendance of the specific detection object is judged.
7. An intelligent attendance device, comprising:
an image acquisition unit configured to acquire image information including a plurality of detection objects;
the image recognition module is used for carrying out face recognition processing on the image information and processing the image information to generate a grid-shaped position map according to the recognized face positions of all detection objects;
and the attendance checking detection module is used for comparing the faces in the grids corresponding to the two graphs according to the latticed position graph and the predetermined latticed seat graph, judging the matching degree of the detection objects in the corresponding grids and obtaining an attendance checking result.
8. The apparatus of claim 7, wherein the image recognition module comprises:
the face recognition submodule is used for carrying out recognition processing on the image information and determining the positions of all faces in the image information;
and the position map generation submodule is used for cutting the image information into a grid-shaped position map comprising a plurality of grids according to the positions of all the human faces, and each grid comprises a group of human face information.
9. The apparatus of claim 8,
dividing according to the seat position of each detection object to obtain the grid-shaped seat map, wherein each grid in the grid-shaped seat map comprises a face sample and basic information corresponding to the seat position;
the attendance checking detection module compares the face information in each grid in the latticed position diagram with the face samples in the corresponding grid in the latticed seat diagram, and judges the attendance state of the detection object corresponding to each grid according to the comparison result.
10. The apparatus according to claim 9, wherein if the similarity between the face information in the grid-like position map and the face sample in the corresponding grid in the grid-like position map is greater than a preset matching degree, it is determined that the corresponding detection object in the grid is on duty, and the identity information of the face information is determined according to the basic information corresponding to the face sample; and if the similarity is smaller than the matching degree or no face information exists in the grid-shaped position diagram, judging that the corresponding detection object in the grid is absent.
11. The apparatus of claim 7, further comprising:
the statistical module is used for continuously obtaining the attendance checking result within a preset time period, and performing statistics to obtain a preset attendance checking result;
and the data sending module is used for sending the preset attendance checking result to a terminal and displaying the preset attendance checking result on the terminal.
12. The apparatus of claim 7, further comprising:
and the attendance counting module is used for continuously obtaining the attendance result within a preset time period, counting the attendance absence time of each detection object within the preset time period, and judging that the specific detection object is absent if the attendance absence time of the specific detection object is greater than a preset attendance absence time threshold value.
13. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 6 when executing the program.
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