CN110889908A - Intelligent sign-in system integrating face recognition and data analysis - Google Patents

Intelligent sign-in system integrating face recognition and data analysis Download PDF

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CN110889908A
CN110889908A CN201911255337.6A CN201911255337A CN110889908A CN 110889908 A CN110889908 A CN 110889908A CN 201911255337 A CN201911255337 A CN 201911255337A CN 110889908 A CN110889908 A CN 110889908A
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face
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CN110889908B (en
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吴仁超
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Suzhou Yudeshui Electric Technology Co Ltd
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吴仁超
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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
    • 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
    • G06V40/161—Detection; Localisation; Normalisation
    • 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
    • G06V40/161—Detection; Localisation; Normalisation
    • G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
    • 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
    • G06V40/174—Facial expression recognition

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Abstract

The invention belongs to the technical field of face recognition, and particularly discloses an intelligent check-in system integrating face recognition and data analysis, which comprises check-in equipment, a face recognition end and a spirit degree evaluation end, wherein the face recognition end is used for recognizing, extracting and comparing face information, the spirit degree evaluation end is used for collecting and analyzing face images and evaluating the spirit degree of check-in personnel, and the check-in equipment is used for collecting the face information. Also can let the staff feel the warmth of enterprise, can the effectual efficiency that improves work.

Description

Intelligent sign-in system integrating face recognition and data analysis
Technical Field
The invention relates to the technical field of face recognition, in particular to an intelligent sign-in system integrating face recognition and data analysis.
Background
The face recognition technology is a series of related technologies which utilize a camera or a camera to collect images or video streams containing a face, automatically detect and track the face in the images and further perform face recognition on the detected face;
in order to standardize personnel management of companies, enterprises, schools and the like, a check-in mode is often adopted, the current check-in mode has substitute signing and fake signing, so that personnel management is disordered, face recognition is the most safe, convenient and standardized recognition check-in mode at present, and the face recognition check-in system in the prior art has the following problems in use:
1. the existing face recognition check-in system only can realize the face recognition check-in function, has single function, cannot know the emotion of staff, cannot know the working state of the staff, possibly reduces the working efficiency of the staff and cannot deal with the staff;
2. the existing face recognition device is huge in size, and the smaller face recognition check-in device cannot be adjusted according to the height of a check-in person;
therefore, an intelligent check-in system combining face recognition and data analysis is urgently needed to solve the problems.
Disclosure of Invention
The invention aims to provide an intelligent sign-in system integrating face recognition and data analysis, and aims to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: an intelligent check-in system integrating face recognition and data analysis comprises check-in equipment, a face recognition end, an image processing module, a database and a mental degree evaluation end;
the system comprises a face recognition terminal, an image processing module, a database, a mental degree evaluation terminal and a check-in device, wherein the face recognition terminal is used for recognizing, extracting and comparing face information, the image processing module is used for processing an acquired face image, the database is used for storing acquired face image data and processed face image data, the mental degree evaluation terminal is used for acquiring and analyzing the face image and evaluating the mental degree of check-in personnel, and the check-in device is used for acquiring the face information;
the output end of the attendance device is electrically connected with the input end of the image processing module, and the output end of the image processing module is electrically connected with the input ends of the face recognition end, the database and the mental degree evaluation end.
As a preferred technical scheme, the spirit degree evaluation terminal is used for evaluating the spirit degree of the check-in personnel, and the total score of the spirit degree evaluation is Z, so that an enterprise manager can select whether the check-in personnel performs more important work or not on the same day according to the spirit state of the check-in personnel, and the problem that the enterprise is lost due to errors in the working process caused by poor spirit state can be effectively avoided;
the mental degree evaluation terminal comprises data analysis and machine learning, the data analysis is used for analyzing all face image data collected by the check-in equipment and judging the mental state of check-in personnel, the machine learning is used for adding labels to face graphic information input in the database, and the mental degree of the check-in personnel is evaluated by two evaluation modes, so that the mental degree evaluation result is more accurate, and an enterprise can know the states of the staff more clearly.
As a preferred technical scheme, the data analysis comprises a model establishing unit, a reference surface establishing unit, a distance measuring unit, a data comparing unit and a data calculating unit;
the model establishing unit is used for establishing a human face image 3D model according to human face image data collected by the check-in equipment, the datum plane establishing unit is used for establishing vertical datum planes according to different positions of the established human face image 3D model, the distance measuring unit is used for measuring the distance between every two datum planes, the data comparing unit is used for comparing the distance measured by the distance measuring unit with a set threshold value, and the data calculating unit is used for evaluating the spiritedness of check-in personnel according to the distance comparison;
the output end of the model establishing unit is electrically connected with the input end of the reference surface establishing unit, the output end of the reference surface establishing unit is electrically connected with the input end of the distance measuring unit, the output end of the distance measuring unit is electrically connected with the input end of the data comparing unit, the output end of the data calculating unit is electrically connected with the input end of the data comparing unit, and the data calculating unit is electrically connected with the database.
The data analysis can effectively judge the mental state of the check-in personnel from the facial expression of the check-in personnel, when the mental state of the check-in personnel is not good, the eyebrow wrinkling phenomenon can occur to the two eyebrows, the eyebrow spacing is reduced, meanwhile, when the check-in personnel stay up all night, the two eyes can be red and swollen, the two eyes cannot be opened as normal, and the opening angle of the two eyes is reduced.
Preferably, the reference plane establishing unit establishes a first reference plane, a second reference plane, a third reference plane and a fourth reference plane, the first reference plane and the second reference plane are vertical reference planes, the third reference plane and the fourth reference plane are horizontal reference planes, the reference point of the first reference plane is the rightmost point of the eyebrows on the left side of the human face, the reference point of the second reference plane is the leftmost point of the eyebrows on the right side of the human face, the reference point of the third reference plane is the lowest point of the upper eyelid, and the reference point of the fourth reference plane is the highest point of the lower eyelid;
the distance measuring unit is used for measuring the distance between a first reference surface and a second reference surface and the distance between a third reference surface and a fourth reference surface, the distance between the first reference surface and the second reference surface is X, the distance between the third reference surface and the fourth reference surface is Y, and the proportionality coefficient of the distance X to the mental degree evaluation total score Z is k1The distance Y accounts for the proportionality coefficient of the mental degree evaluation total score Z and is k2，k1And k2The confirmation of (2) is realized by questionnaire;
the threshold value of the distance X between the first reference surface and the second reference surface is m, the threshold value of the distance Y between the third reference surface and the fourth reference surface is n, the mental degree variation of the unit difference of the distance X and the threshold value m is a, and the mental degree variation of the unit difference of the distance Y and the threshold value n is b;
according to the formula:
Figure 201611DEST_PATH_IMAGE002
wherein A is the spirit degree determined by the distance X between the first reference surface and the second reference surface;
according to the formula:
Figure 197380DEST_PATH_IMAGE004
b is the spirit determined by the distance Y between the third reference surface and the fourth reference surface;
according to the formula:
Figure 508275DEST_PATH_IMAGE006
wherein C represents the total mental degree value of the check-in personnel;
when C is more than or equal to C, the spirituality of the check-in personnel is good, and the normal work is not influenced;
when C < C, the mental degree of the check-in personnel is not good, the working efficiency is influenced, even errors occur in work, and the manager can choose to give the staff a rest or approve rest.
Each group of data analysis is compared aiming at personal data, the condition that the eyebrow space and the canthus opening angle of each person are inconsistent is avoided, the data analysis is carried out to evaluate the spiritedness of the check-in personnel only when the face recognition is passed, the check-in personnel with lower spiritedness evaluation send the information and the state of the check-in personnel to the client, and the management personnel judge the check-in personnel.
As a preferred technical scheme, the machine learning comprises a data calling unit, a data storage unit, face image data, a label adding unit and an input unit;
the data calling unit is used for calling the face picture data from the database and providing the face picture data for a manager to refer, the input unit is used for the manager to input a corresponding mental state value according to the face picture data of a registered person, the tag adding unit is used for adding a tag to the face picture data according to the mental state value input by the input unit and indicating that the face picture data is in a bad mental state, the data storage unit is used for storing the face picture data added with the tag into the database and providing the system for learning to inform the manager that the face picture data of the registered person next time is in a bad mental state;
the data retrieval system comprises a data retrieval unit, a data base, an input unit, a label adding unit, a data storage unit and a data retrieval unit, wherein the data retrieval unit is electrically connected with the data base, the data retrieval unit retrieves human face picture data from the data base, the output end of the input unit is electrically connected with the input end of the label adding unit, the output end of the label adding unit is electrically connected with the input end of the human face picture data, the output end of the human face picture data is electrically connected with the input end of the data storage unit, and the output end of the data.
Utilize machine learning, through administrator's artificial judgement, add the label to personnel's of registering face information, reduce and appear frowning phenomenon and lead to the judgement error when face identification, can effectual improvement spiritual degree evaluation's the degree of accuracy, provide dual guarantee.
As a preferred technical scheme, the face recognition end comprises a feature extraction unit, a data conversion unit, a feature comparison unit and a result output unit;
the system comprises a feature extraction unit, a data conversion unit, a feature comparison unit, a result output unit and a comparison unit, wherein the feature extraction unit is used for extracting face feature data with identification degree from face graphic data collected by check-in equipment, the data conversion unit is used for converting feature parts in the face graphic data extracted by the feature extraction unit into data capable of being compared, the feature comparison unit is used for comparing the data extracted by the feature extraction unit with data stored in the data and confirming the identity of a check-in person, and the result output unit is used for outputting the comparison result;
the output end of the feature extraction unit is electrically connected with the input end of the data conversion unit, the output end of the data conversion unit is electrically connected with the input end of the feature comparison unit, and the output end of the feature comparison unit is electrically connected with the input end of the result output unit.
As a preferred technical scheme, the result output unit comprises a display screen and a voice broadcasting unit;
the display screen is used for displaying the human face, and the voice broadcast unit is used for carrying out voice broadcast on whether the staff that registers successfully registers or not and encouraging the staff with low mental state evaluation.
According to the technical scheme, the attendance checking device comprises a base, an L-shaped fixing plate is arranged at the rear end of the base, a measuring rod is mounted above the L-shaped fixing plate, an adjusting part is arranged inside the base, a display panel is mounted at the front end of the base through a hinge, a display screen is embedded in the display panel, a camera is mounted at the top end of the display screen, and the camera is used for collecting face images.
As a preferred technical scheme, a human body infrared sensor is arranged at the top end of the measuring rod and used for detecting whether a check-in person approaches to check-in equipment or not, the bottom of the L-shaped fixed plate is provided with a driving motor, the upper surface of the base is provided with a sliding groove, one end of the driving motor is fixedly provided with a threaded rod through a key connection, the outer side of the threaded rod is provided with a sliding block through a thread, the sliding block slides in the sliding groove, a supporting block is arranged above the sliding block and used for supporting the display panel, the upper surface of the base is provided with a controller, the output end of the infrared human body sensor is electrically connected with the input end of the controller, the output electric connection of controller drive motor's input, the output electric connection of camera controller's input, the output electric connection of controller display screen's input.
As a preferred technical scheme, a rotating roller is rotatably arranged on one side, close to the display panel, of the top end of the supporting block, and the rotating roller is in rolling contact with the display panel, so that the friction force between the supporting block and the display panel is reduced, and the angle adjustment of the display panel is smoother.
Compared with the prior art, the invention has the beneficial effects that:
1. be provided with the spirit degree evaluation end, can utilize data analysis and machine learning two kinds of modes to evaluate the spirit degree of personnel of registering to can send the evaluation result to the customer end and show, the administrator can be according to the spirit degree that shows, to the relatively poor staff of mental state take a rest, reduces the probability of making mistakes in the work, also can let the staff feel the warmth of enterprise, can effectual improvement work efficiency, reduce the low problem of making mistakes in work efficiency and the working process that leads to because of the not good problem of mental state.
2. Be provided with equipment of registering, utilize adjusting part, can effectually adjust camera and display screen and height and angle for the personnel of registering that equipment of registering can be applicable to different heights, make the people's face image that the camera was gathered clear more and comprehensive, simultaneously, utilize the live-rollers to reduce the frictional force between sliding block and the display panel, make the sliding block more smooth and easy to the regulation of display panel angle, can not appear blocking and pausing phenomenon at the in-process that removes.
Drawings
FIG. 1 is a schematic diagram of a module composition of an intelligent check-in system integrating face recognition and data analysis according to the present invention;
FIG. 2 is a schematic diagram of module connection of an intelligent check-in system integrating face recognition and data analysis according to the present invention;
FIG. 3 is a schematic structural diagram of an intelligent check-in system check-in device integrating face recognition and data analysis according to the present invention;
FIG. 4 is a schematic structural diagram of an adjustment component of an intelligent check-in system integrating face recognition and data analysis according to the present invention.
Reference numbers in the figures: 1. a base; 2. an L-shaped fixing plate; 3. a drive motor; 4. a sliding groove; 5. a threaded rod; 6. a slider; 7. a support block; 8. a rotating roller; 9. a display panel; 10. a display screen; 11. a camera; 12. a measuring rod; 13. a human body infrared sensor; 14. and a controller.
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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 first embodiment is as follows: as shown in fig. 1-2, an intelligent check-in system integrating face recognition and data analysis comprises a check-in device, a face recognition terminal, an image processing module, a database and a mental degree evaluation terminal;
the system comprises a face recognition terminal, an image processing module, a database, a mental degree evaluation terminal and a check-in device, wherein the face recognition terminal is used for recognizing, extracting and comparing face information, the image processing module is used for processing an acquired face image, the database is used for storing acquired face image data and processed face image data, the mental degree evaluation terminal is used for acquiring and analyzing the face image and evaluating the mental degree of check-in personnel, and the check-in device is used for acquiring the face information;
the output end of the attendance device is electrically connected with the input end of the image processing module, and the output end of the image processing module is electrically connected with the input ends of the face recognition end, the database and the mental degree evaluation end.
The spirit degree evaluation terminal is used for evaluating the spirit degree of the check-in personnel, and the total score of the spirit degree evaluation is Z =100, so that an enterprise manager can select whether the check-in personnel can perform more important work or not on the same day according to the spirit state of the check-in personnel, and the problem that errors occur in the working process due to poor spirit state and the loss of enterprises is caused can be effectively avoided;
the mental degree evaluation terminal comprises data analysis, and the data analysis is used for analyzing the face image data collected by the check-in equipment and judging the mental state of the check-in personnel.
The data analysis comprises a model establishing unit, a reference surface establishing unit, a distance measuring unit, a data comparing unit and a data calculating unit;
the model establishing unit is used for establishing a human face image 3D model according to human face image data collected by the check-in equipment, the datum plane establishing unit is used for establishing vertical datum planes according to different positions of the established human face image 3D model, the distance measuring unit is used for measuring the distance between every two datum planes, the data comparing unit is used for comparing the distance measured by the distance measuring unit with a set threshold value, and the data calculating unit is used for evaluating the spiritedness of check-in personnel according to the distance comparison;
the output end of the model establishing unit is electrically connected with the input end of the reference surface establishing unit, the output end of the reference surface establishing unit is electrically connected with the input end of the distance measuring unit, the output end of the distance measuring unit is electrically connected with the input end of the data comparing unit, the output end of the data calculating unit is electrically connected with the input end of the data comparing unit, and the data calculating unit is electrically connected with the database.
The datum plane establishing unit establishes a first datum plane, a second datum plane, a third datum plane and a fourth datum plane, wherein the first datum plane and the second datum plane are vertical datum planes, the third datum plane and the fourth datum plane are horizontal datum planes, the datum point of the first datum plane is the rightmost point of the eyebrows on the left side of the human face, the datum point of the second datum plane is the leftmost point of the eyebrows on the right side of the human face, the datum point of the third datum plane is the lowest point of the upper eyelid, and the datum point of the fourth datum plane is the uppermost point of the lower eyelid;
based on the King sign-in, the distance measuring unit is used for measuring the distance between a first reference surface and a second reference surface and the distance between a third reference surface and a fourth reference surface, the distance between the first reference surface and the second reference surface is X =2.8cm, the distance between the third reference surface and the fourth reference surface is Y =0.8cm, and the proportionality coefficient of the distance X to the mental degree evaluation total score Z is k1K is the proportionality coefficient of distance Y to total score Z of mental degree evaluation2=0.35，k1And k2The confirmation is realized by questionnaire survey and comparison;
a threshold value of a distance X =2.8cm between the first reference plane and the second reference plane is m =3cm, a threshold value of a distance Y =0.8cm between the third reference plane and the fourth reference plane is n =0.9cm, a mental degree variation of 0.025cm in a unit difference between the distance X and the threshold value m is a =5, and a mental degree variation of 0.05 in a unit difference between the distance Y and the threshold value n is b = 5;
according to the formula:
Figure 169064DEST_PATH_IMAGE008
wherein a =55 is the mental degree determined by the distance X =2.8 between the first reference plane and the second reference plane;
according to the formula:
Figure 796485DEST_PATH_IMAGE010
wherein B =25 is the mental degree determined by the distance Y between the third reference plane and the fourth reference plane;
according to the formula:
Figure DEST_PATH_IMAGE012
wherein C =80 represents a total mental value of the check-in person;
when C is more than or equal to 80, the spirituality of the check-in personnel is good, and the normal work is not influenced.
Example two: as shown in fig. 1-2, an intelligent check-in system integrating face recognition and data analysis comprises a check-in device, a face recognition terminal, an image processing module, a database and a mental degree evaluation terminal;
the system comprises a face recognition terminal, an image processing module, a database, a mental degree evaluation terminal and a check-in device, wherein the face recognition terminal is used for recognizing, extracting and comparing face information, the image processing module is used for processing an acquired face image, the database is used for storing acquired face image data and processed face image data, the mental degree evaluation terminal is used for acquiring and analyzing the face image and evaluating the mental degree of check-in personnel, and the check-in device is used for acquiring the face information;
the output end of the attendance device is electrically connected with the input end of the image processing module, and the output end of the image processing module is electrically connected with the input ends of the face recognition end, the database and the mental degree evaluation end.
The spirit degree evaluation terminal is used for evaluating the spirit degree of the check-in personnel, and the total score of the spirit degree evaluation is Z =100, so that an enterprise manager can select whether the check-in personnel can perform more important work or not on the same day according to the spirit state of the check-in personnel, and the problem that errors occur in the working process due to poor spirit state and the loss of enterprises is caused can be effectively avoided;
the mental degree evaluation terminal comprises data analysis, and the data analysis is used for analyzing the face image data collected by the check-in equipment and judging the mental state of the check-in personnel.
The data analysis comprises a model establishing unit, a reference surface establishing unit, a distance measuring unit, a data comparing unit and a data calculating unit;
the model establishing unit is used for establishing a human face image 3D model according to human face image data collected by the check-in equipment, the datum plane establishing unit is used for establishing vertical datum planes according to different positions of the established human face image 3D model, the distance measuring unit is used for measuring the distance between every two datum planes, the data comparing unit is used for comparing the distance measured by the distance measuring unit with a set threshold value, and the data calculating unit is used for evaluating the spiritedness of check-in personnel according to the distance comparison;
the output end of the model establishing unit is electrically connected with the input end of the reference surface establishing unit, the output end of the reference surface establishing unit is electrically connected with the input end of the distance measuring unit, the output end of the distance measuring unit is electrically connected with the input end of the data comparing unit, the output end of the data calculating unit is electrically connected with the input end of the data comparing unit, and the data calculating unit is electrically connected with the database.
The datum plane establishing unit establishes a first datum plane, a second datum plane, a third datum plane and a fourth datum plane, wherein the first datum plane and the second datum plane are vertical datum planes, the third datum plane and the fourth datum plane are horizontal datum planes, the datum point of the first datum plane is the rightmost point of the eyebrows on the left side of the human face, the datum point of the second datum plane is the leftmost point of the eyebrows on the right side of the human face, the datum point of the third datum plane is the lowest point of the upper eyelid, and the datum point of the fourth datum plane is the uppermost point of the lower eyelid;
the distance measuring unit is used for measuring the distance between a first reference surface and a second reference surface and the distance between a third reference surface and a fourth reference surface, and the second reference surface is used for detecting the distance between the first reference surface and the second reference surface and the distance between the third reference surface and the fourth reference surfaceThe distance between a reference surface and a second reference surface is X =2.7cm, the distance between a third reference surface and a fourth reference surface is Y =0.7cm, and the distance X accounts for the proportionality coefficient of the total score Z of the mental degree evaluation and is k1K is the proportionality coefficient of distance Y to total score Z of mental degree evaluation2=0.45，k1And k2The confirmation of (2) is realized by questionnaire;
a threshold value of the distance X =2.7 between the first reference plane and the second reference plane is m =2.65cm, a threshold value of the distance Y =0.7 between the third reference plane and the fourth reference plane is n =0.65cm, a mental degree variation of 0.05 in a unit difference between the distance X and the threshold value m is a =5, and a mental degree variation of 0.025 in a unit difference between the distance Y and the threshold value n is b = 5;
according to the formula:
Figure DEST_PATH_IMAGE014
wherein a =55 is the spirit determined by the distance X between the first reference plane and the second reference plane;
according to the formula:
Figure DEST_PATH_IMAGE016
wherein B =45 is the spirit determined by the distance Y between the third reference plane and the fourth reference plane;
according to the formula:
Figure DEST_PATH_IMAGE018
wherein C =100 represents a total mental value of the check-in person;
when C is more than or equal to 80, the spirituality of the check-in personnel is good, and the normal work is not influenced.
Example three: as shown in fig. 1-2, an intelligent check-in system integrating face recognition and data analysis comprises a check-in device, a face recognition terminal, an image processing module, a database and a mental degree evaluation terminal;
the system comprises a face recognition terminal, an image processing module, a database, a mental degree evaluation terminal and a check-in device, wherein the face recognition terminal is used for recognizing, extracting and comparing face information, the image processing module is used for processing an acquired face image, the database is used for storing acquired face image data and processed face image data, the mental degree evaluation terminal is used for acquiring and analyzing the face image and evaluating the mental degree of check-in personnel, and the check-in device is used for acquiring the face information;
the output end of the attendance device is electrically connected with the input end of the image processing module, and the output end of the image processing module is electrically connected with the input ends of the face recognition end, the database and the mental degree evaluation end.
The mental degree evaluation terminal comprises machine learning, and the machine learning is used for adding labels to the face graphic information input in the database.
The machine learning comprises a data calling unit, a data storage unit, face picture data, a label adding unit and an input unit;
the data calling unit is used for calling the face picture data from the database and providing the face picture data for a manager to refer, the input unit is used for the manager to input a corresponding mental state value according to the face picture data of a registered person, the tag adding unit is used for adding a tag to the face picture data according to the mental state value input by the input unit and indicating that the face picture data is in a bad mental state, the data storage unit is used for storing the face picture data added with the tag into the database and providing the system for learning to inform the manager that the face picture data of the registered person next time is in a bad mental state;
the data retrieval system comprises a data retrieval unit, a data base, an input unit, a label adding unit, a data storage unit and a data retrieval unit, wherein the data retrieval unit is electrically connected with the data base, the data retrieval unit retrieves human face picture data from the data base, the output end of the input unit is electrically connected with the input end of the label adding unit, the output end of the label adding unit is electrically connected with the input end of the human face picture data, the output end of the human face picture data is electrically connected with the input end of the data storage unit, and the output end of the data.
The face recognition end comprises a feature extraction unit, a data conversion unit, a feature comparison unit and a result output unit;
the system comprises a feature extraction unit, a data conversion unit, a feature comparison unit, a result output unit and a comparison unit, wherein the feature extraction unit is used for extracting face feature data with identification degree from face graphic data collected by check-in equipment, the data conversion unit is used for converting feature parts in the face graphic data extracted by the feature extraction unit into data capable of being compared, the feature comparison unit is used for comparing the data extracted by the feature extraction unit with data stored in the data and confirming the identity of a check-in person, and the result output unit is used for outputting the comparison result;
the output end of the feature extraction unit is electrically connected with the input end of the data conversion unit, the output end of the data conversion unit is electrically connected with the input end of the feature comparison unit, and the output end of the feature comparison unit is electrically connected with the input end of the result output unit.
The result output unit comprises a display screen and a voice broadcasting unit;
the display screen is used for displaying the human face, and the voice broadcast unit is used for carrying out voice broadcast on whether the staff that registers successfully registers or not and encouraging the staff with low mental state evaluation.
Example four: as shown in fig. 3-4, the equipment of registering includes base 1, and base 1 rear end is provided with L type fixed plate 2, and measuring stick 12 is installed to L type fixed plate 2 top, and base 1 is inside to be provided with adjusting part, and base 1 front end is installed display panel 9 through the articulated, and display panel 9 is inside to be installed in the embedding, and camera 11 is installed on the display screen 10 top, and camera 11 is used for gathering the face image.
Human infrared inductor 13 is installed on 11 tops of measuring stick, human infrared inductor 13 is used for detecting whether being close to the equipment of registering to the personnel of registering, driving motor 3 is installed to 2 bottoms of L type fixed plate, sliding tray 4 has been seted up to base 1 upper surface, 3 one end of driving motor has threaded rod 5 through key-type connection fixed mounting, sliding block 6 is installed through the screw thread in the threaded rod 5 outside, sliding block 6 slides in sliding tray 4 inside, sliding block 6 top is provided with supporting shoe 7, supporting shoe 7 is used for supporting display panel 9, 1 upper surface of base has controller 14, infrared human inductor 13's output electric connection controller 14's input, controller 14's output electric connection driving motor 3's input, camera 11's output electric connection controller 14's input, controller 14's output electric connection display screen 9's input.
The top end of the supporting block 7 is rotatably provided with a rotating roller 8 close to one side of the display board 9, the rotating roller 8 is in rolling contact with the display board 9, and the friction force between the supporting block 7 and the display board 9 is reduced, so that the angle adjustment of the display board 9 is smoother.
The working principle is as follows: when the sign-in equipment is used, whether a person who signs in is close to the equipment is sensed by the human body infrared sensor 13, when the person who signs in is sensed to be close to the equipment, the controller 14 controls the driving motor 3 to rotate, so that the driving motor 3 drives the threaded rod 5 to rotate, the sliding block 6 slides back and forth in the sliding groove 4 by the rotation of the threaded rod 5, the position of the supporting block 7 for supporting the display panel 9 is changed, the adjustment of the display angle of the display panel 9 is realized, meanwhile, when the camera 11 cannot acquire a complete face image and cannot perform face recognition, the display screen 10 transmits a signal to the controller 14, the controller 14 controls the driving motor 3 to rotate again, the angle of the display panel 9 is adjusted again, the face image acquired by the camera 11 can be clearer and more complete, and meanwhile, the friction force between the supporting block 7 and the display panel 9 is reduced by the rotating roller 8, so that the adjustment of the display panel 9 is smoother.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (10)

1. The utility model provides a system of registering of intelligence of integration face identification and data analysis which characterized in that: the check-in system comprises check-in equipment, a face recognition end, an image processing module, a database and a mental degree evaluation end;
the system comprises a face recognition terminal, an image processing module, a database, a mental degree evaluation terminal and a check-in device, wherein the face recognition terminal is used for recognizing, extracting and comparing face information, the image processing module is used for processing an acquired face image, the database is used for storing acquired face image data and processed face image data, the mental degree evaluation terminal is used for acquiring and analyzing the face image and evaluating the mental degree of check-in personnel, and the check-in device is used for acquiring the face information;
the output end of the attendance device is electrically connected with the input end of the image processing module, and the output end of the image processing module is electrically connected with the input ends of the face recognition end, the database and the mental degree evaluation end.
2. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 1, wherein: the spirit degree evaluation terminal is used for evaluating the spirit degree of the check-in personnel, and the total score of the spirit degree evaluation is Z;
the mental degree evaluation terminal comprises data analysis and machine learning, wherein the data analysis is used for analyzing the face image data collected by the check-in equipment and judging the mental state of the check-in personnel, and the machine learning is used for adding labels to the face image information input in the database.
3. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 2, wherein: the data analysis comprises a model establishing unit, a reference surface establishing unit, a distance measuring unit, a data comparing unit and a data calculating unit;
the model establishing unit is used for establishing a human face image 3D model according to human face image data collected by the check-in equipment, the datum plane establishing unit is used for establishing datum planes according to different positions of the established human face image 3D model, the distance measuring unit is used for measuring the distance between every two datum planes, the data comparing unit is used for comparing the distance measured by the distance measuring unit with a set threshold value, and the data calculating unit is used for evaluating the spiritedness of check-in personnel according to the distance comparison;
the output end of the model establishing unit is electrically connected with the input end of the reference surface establishing unit, the output end of the reference surface establishing unit is electrically connected with the input end of the distance measuring unit, the output end of the distance measuring unit is electrically connected with the input end of the data comparing unit, the output end of the data calculating unit is electrically connected with the input end of the data comparing unit, and the data calculating unit is electrically connected with the database.
4. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 3, wherein: the datum plane establishing unit establishes a first datum plane, a second datum plane, a third datum plane and a fourth datum plane, wherein the first datum plane and the second datum plane are vertical datum planes, the third datum plane and the fourth datum plane are horizontal datum planes, the datum point of the first datum plane is the rightmost point of the eyebrows on the left side of the human face, the datum point of the second datum plane is the leftmost point of the eyebrows on the right side of the human face, the datum point of the third datum plane is the lowest point of the upper eyelid, and the datum point of the fourth datum plane is the uppermost point of the lower eyelid;
the distance measuring unit is used for measuring the distance between a first reference surface and a second reference surface and the distance between a third reference surface and a fourth reference surface, the distance between the first reference surface and the second reference surface is X, the distance between the third reference surface and the fourth reference surface is Y, and the proportionality coefficient of the distance X to the mental degree evaluation total score Z is k1The distance Y accounts for the proportionality coefficient of the mental degree evaluation total score Z and is k2，k1And k2The confirmation is determined by questionnaire survey and comparison;
the threshold value of the distance X between the first reference surface and the second reference surface is m, the threshold value of the distance Y between the third reference surface and the fourth reference surface is n, the mental degree variation of the unit difference of the distance X and the threshold value m is a, and the mental degree variation of the unit difference of the distance Y and the threshold value n is b;
according to the formula:
Figure 715481DEST_PATH_IMAGE002
wherein A is the spirit degree determined by the distance X between the first reference surface and the second reference surface;
according to the formula:
Figure 436882DEST_PATH_IMAGE004
b is the spirit determined by the distance Y between the third reference surface and the fourth reference surface;
according to the formula:
Figure DEST_PATH_IMAGE006
wherein C represents the total mental degree value of the check-in personnel;
when C is more than or equal to C, the spirituality of the check-in personnel is good, and the normal work is not influenced;
when C < C, the mental degree of the check-in personnel is not good, the working efficiency is influenced, even errors occur in work, and the manager can choose to give the staff a rest or approve rest.
5. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 2, wherein the machine learning comprises a data retrieving unit, a data storing unit, face picture data, a tag adding unit and an input unit;
the data calling unit is used for calling the face picture data from the database and providing the face picture data for a manager to refer, the input unit is used for the manager to input a corresponding mental state value according to the face picture data of a registered person, the tag adding unit is used for adding a tag to the face picture data according to the mental state value input by the input unit and indicating that the face picture data is in a bad mental state, the data storage unit is used for storing the face picture data added with the tag into the database and providing the system for learning to inform the manager that the face picture data of the registered person next time is in a bad mental state;
the data retrieval system comprises a data retrieval unit, a data base, an input unit, a label adding unit, a data storage unit and a data retrieval unit, wherein the data retrieval unit is electrically connected with the data base, the data retrieval unit retrieves human face picture data from the data base, the output end of the input unit is electrically connected with the input end of the label adding unit, the output end of the label adding unit is electrically connected with the input end of the human face picture data, the output end of the human face picture data is electrically connected with the input end of the data storage unit, and the output end of the data.
6. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 1, wherein: the face recognition end comprises a feature extraction unit, a data conversion unit, a feature comparison unit and a result output unit;
the system comprises a feature extraction unit, a data conversion unit, a feature comparison unit, a result output unit and a comparison unit, wherein the feature extraction unit is used for extracting face feature data with identification degree from face graphic data collected by check-in equipment, the data conversion unit is used for converting feature parts in the face graphic data extracted by the feature extraction unit into data capable of being compared, the feature comparison unit is used for comparing the data extracted by the feature extraction unit with data stored in the data and confirming the identity of a check-in person, and the result output unit is used for outputting the comparison result;
the output end of the feature extraction unit is electrically connected with the input end of the data conversion unit, the output end of the data conversion unit is electrically connected with the input end of the feature comparison unit, and the output end of the feature comparison unit is electrically connected with the input end of the result output unit.
7. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 6, wherein: the result output unit comprises a display screen and a voice broadcasting unit;
the display screen is used for displaying the human face, and the voice broadcast unit is used for carrying out voice broadcast on whether the staff that registers successfully registers or not and encouraging the staff with low mental state evaluation.
8. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 1, wherein: the equipment of registering includes base (1), base (1) rear end is provided with L type fixed plate (2), measuring stick (12) are installed to L type fixed plate (2) top, the inside regulating part that is provided with of base (1), base (1) front end installs display panel (9) through the articulated, display screen (10) are installed to display panel (9) inside embedding, camera (11) are installed on display screen (10) top.
9. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 8, wherein: the human body infrared sensor (13) is installed at the top end of the measuring rod (11), the driving motor (3) is installed at the bottom of the L-shaped fixing plate (2), a sliding groove (4) is formed in the upper surface of the base (1), a threaded rod (5) is fixedly installed at one end of the driving motor (3) through key connection, a sliding block (6) is installed on the outer side of the threaded rod (5) through threads, the sliding block (6) slides in the sliding groove (4), a supporting block (7) is arranged above the sliding block (6), a controller (14) is installed on the upper surface of the base (1), the output end of the infrared human body sensor (13) is electrically connected with the input end of the controller (14), the output end of the controller (14) is electrically connected with the input end of the driving motor (3), and the output end of the camera (11) is electrically connected with the input end of the, the output end of the controller (14) is electrically connected with the input end of the display screen (9).
10. The intelligent check-in system integrating face recognition and data analysis as claimed in claim 9, wherein: and a rotating roller (8) is rotatably arranged at one side of the top end of the supporting block (7) close to the display plate (9).
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