An intelligent production station screen based on face recognition technology

Abstract

The present invention provides an intelligent production workstation screen based on face recognition technology, including: a screen for collecting verified facial information of workers, identifying the worker identity of the corresponding worker according to the verified facial information, generating corresponding execution task information based on the worker identity, and transmitting the execution task information to a preset display area for display, collecting work data of each of the workers in different preset time periods, establishing work feedback information, and adjusting the corresponding pre-execution task information of each of the workers in the next preset period based on the work feedback information. By using face recognition technology, the worker identity can be quickly identified, and the corresponding production process, process parameters and other information can be automatically retrieved, thereby improving production speed and quality.

Description

Technical Field

[0001] The present invention relates to the field of face recognition technology, and in particular to an intelligent production station screen based on face recognition technology. Background Art

[0002] The demand for clothing in the domestic and foreign markets has increased significantly. With the progress of the times and the development of Corgi, more and more clothing processing factories have emerged, so a large number of workers are needed to carry out clothing processing. Since clothing processing is a relatively single job, each type of worker processes different parts of the clothes, and finally sews them together to produce clothing. However, due to the large number of workers in the production process, it is inconvenient to manage, so a convenient and effective management device is needed.

[0003] Therefore, the present invention provides an intelligent production workstation screen based on face recognition technology. Summary of the invention

[0004] The present invention provides an intelligent production workstation screen based on face recognition technology. By using face recognition technology, the identity of workers can be quickly identified, and corresponding production process, process parameters and other information can be automatically retrieved to improve production speed and quality.

[0005] The present invention provides an intelligent production station screen based on face recognition technology, comprising:

[0006] An identity recognition module, used to collect verification identification information of a worker and identify the worker identity of the corresponding worker according to the verification identification information;

[0007] A task issuing module, used to generate corresponding task execution information based on the worker identity, and transmit the task execution information to a preset display area for display;

[0008] A supervision feedback module is used to collect the work data of each worker in different preset time periods and establish work feedback information;

[0009] A management adjustment module is used to adjust the pre-execution task information corresponding to each of the workers in the next work cycle based on the work feedback information.

[0010] In one practicable manner,

[0011] Also includes:

[0012] Worker station display screen, including: task display sub-screen and information display sub-screen;

[0013] The task display subscreen is used to display the execution task information;

[0014] The information display sub-screen is used to display the worker identity corresponding to each of the workers.

[0015] In one practicable manner,

[0016] Also includes:

[0017] An information input terminal is used to collect facial organ appearance features corresponding to each facial organ dimension of a first-time employee, and establish sample identification information of the first-time employee;

[0018] The basic information of the first-time employee is collected and combined with the sample identification information to establish the worker identity of the first-time employee, and the information is transmitted to the entered information database for storage.

[0019] In one practicable manner,

[0020] The identity recognition module comprises:

[0021] A picture frame correction unit is used to collect an actual facial picture frame corresponding to each of the workers, and to perform correction processing on each of the actual facial picture frames to obtain a corrected facial picture frame corresponding to each of the workers;

[0022] A facial feature matching operation unit is used to analyze the corrected facial image frame to obtain facial organ features of the corresponding worker, and to match corresponding matching identification information to each facial organ feature in the entered information database;

[0023] An identification analysis unit, used to determine whether the plurality of matching identification information corresponding to the same worker are consistent, and if consistent, to search the entered information database for the worker identity corresponding to the matching identification information;

[0024] The reorganized overall recognition unit is used to construct a facial simple group picture of the corresponding worker based on the facial organ features if the several matchable identification information corresponding to the same worker are inconsistent, and search the facial simple group picture in the entered information database to obtain the worker identity corresponding to the worker.

[0025] In one practicable manner,

[0026] The picture frame correction unit comprises:

[0027] A picture frame acquisition and mapping subunit, used for acquiring an actual facial picture frame corresponding to each of the workers, mapping the actual facial picture frame to a preset high-dimensional space to obtain a high-dimensional mapping picture frame, and mapping the actual facial picture frame to a preset low-dimensional space to obtain a low-dimensional mapping picture frame;

[0028] A high- and low-dimensional facial organ distribution determination subunit, configured to obtain a facial contour of a corresponding worker on the actual facial picture frame, obtain a high-dimensional facial organ distribution of the worker in the high-dimensional mapping picture frame, and obtain a low-dimensional facial organ distribution of the worker in the low-dimensional mapping picture frame;

[0029] An iterative correction feature extraction subunit, for performing iterative correction processing on the actual facial picture frame when the distribution features between the high-dimensional facial organ distribution and the low-dimensional facial organ distribution are inconsistent, and collecting the correction distribution features between the corresponding corrected high-dimensional facial organ distribution and the corrected low-dimensional facial organ distribution after each iterative correction processing;

[0030] The iterative correction completion processing subunit is used to stop the iterative correction processing and obtain the corresponding corrected facial image frame when the correction distribution characteristics are consistent.

[0031] In one practicable manner,

[0032] The task issuing module includes:

[0033] An information retrieval unit, configured to retrieve historical work information, work type, and stage work goal of a corresponding worker according to the worker identity, and establish a corresponding workload of the corresponding worker in different past time periods based on the historical work information;

[0034] An efficiency analysis unit is used to retrieve a corresponding work model according to the work type, input the corresponding workload of the corresponding worker in different past time periods into the work model to simulate the historical work efficiency of the corresponding worker in each of the historical time periods, and establish a work efficiency fluctuation chart corresponding to each of the workers;

[0035] A task quantification unit is used to analyze each of the work efficiency fluctuation charts to obtain the predicted work efficiency of the corresponding worker in this time period, and generate the minimum completed task volume of the worker in this time period based on the historical work efficiency and the stage work target;

[0036] The task issuing unit is used to establish the execution task information of the corresponding worker based on the minimum completed task amount and the type of work, and transmit the execution task information to a preset display area for display.

[0037] In one practicable manner,

[0038] The supervisory feedback module comprises:

[0039] A data monitoring unit, used for collecting corresponding work data of each worker in different preset time periods after the worker starts working;

[0040] A finished product monitoring unit, used to analyze each of the work data to obtain the corresponding personal finished product generation amount of the corresponding worker in each preset time period;

[0041] The regional supervision unit is used to count the total finished product generation corresponding to each preset worker group in each preset time period, and to establish work feedback information of the preset worker group in combination with the individual finished product generation.

[0042] In one practicable manner,

[0043] The management adjustment module includes:

[0044] A production analysis unit is used to analyze the work feedback information to obtain the amount that can be completed by each worker group in this work cycle, retrieve the production target corresponding to each worker group, and determine the available working time and the amount of work to be done corresponding to each worker group;

[0045] A work allocation unit is used to establish the group average workload corresponding to the corresponding worker group in each work cycle according to the available working time and the workload to be done, analyze the work feedback information, and obtain the current workload corresponding to each worker in the same worker group;

[0046] A task allocation unit, configured to establish an allocation weight for each of the workers based on the order of the current workload from high to low, and to establish the corresponding allocated workload for each worker in the next work cycle based on the allocation weight and the number of workers in the corresponding worker group;

[0047] The task adjustment unit is used to adjust each of the allocated workloads according to a preset maximum allocation threshold and a minimum allocation threshold, and to establish corresponding pre-execution task information of each of the workers in the next work cycle according to the adjustment result.

[0048] In one practicable manner,

[0049] The task adjustment unit is further used for:

[0050] When each of the allocated workloads is less than the preset maximum allocated workload threshold and greater than the minimum allocated workload threshold, pre-execution task information corresponding to each of the workloads in the next work cycle is established according to the allocated workload.

[0051] In one practicable manner,

[0052] The identity recognition module is also used for:

[0053] The assessment information of the corresponding worker is generated according to the activity information of each worker in the corresponding factory, and the assessment information is transmitted to the preset display area for display.

[0054] The beneficial effects that can be achieved by the present invention are as follows: in order to achieve effective management, when a worker enters the factory and starts working, the worker's verification and identification information is collected to determine the worker's identity, and then the corresponding task execution information is matched for the worker. In order to facilitate the worker to view his or her own task, the task execution information is transmitted to the preset display area on the worker's workstation screen for display. Then, during the worker's work, the work data generated in different time periods is collected, thereby establishing work feedback information. Finally, the task execution information of each worker in the next work cycle is adjusted according to the work feedback information, and production tasks can be reasonably allocated to each employee, which can not only ensure the workload of old employees, but also gradually improve the work efficiency of new employees, thereby improving production speed and quality.

[0055] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0056] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0058] Figure 1 A schematic diagram of the composition of an intelligent production station screen based on face recognition technology in an embodiment of the present invention;

[0059] Figure 2 The present invention is a schematic diagram of the unit composition of an image frame correction of an intelligent production workstation screen based on face recognition technology in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0061] Example 1

[0062] This embodiment provides an intelligent production station screen based on face recognition technology, such as Figure 1 As shown, including:

[0063] An identity recognition module, used to collect verification identification information of a worker and identify the worker identity of the corresponding worker according to the verification identification information;

[0064] A task issuing module, used to generate corresponding task execution information based on the worker identity, and transmit the task execution information to a preset display area for display;

[0065] A supervision feedback module is used to collect the work data of each worker in different preset time periods and establish work feedback information;

[0066] A management adjustment module is used to adjust the pre-execution task information corresponding to each of the workers in the next work cycle based on the work feedback information.

[0067] In this example, the verification identification information represents the collected worker identification information, and one worker corresponds to one verification identification information;

[0068] In this example, the worker identity includes the worker's job type and working hours. One worker corresponds to one worker identity.

[0069] In this example, the execution task information indicates the task that the worker needs to complete this time;

[0070] In this example, the preset time period may be one hour.

[0071] The working principle and beneficial effects of the above technical solution: in order to achieve effective management, when a worker enters the factory and starts working, the worker's verification and identification information is collected to determine the worker's identity, and then the corresponding task execution information is matched for it. In order to facilitate the worker to view his or her own tasks, the task execution information is transmitted to the preset display area on the worker's workstation screen for display. Then, during the worker's work process, the work data generated in different time periods is collected, thereby establishing work feedback information. Finally, according to the work feedback information, the task execution information of each worker in the next work cycle is adjusted, and the production tasks can be reasonably allocated to each employee, which can not only ensure the workload of old employees, but also gradually improve the work efficiency of new employees, thereby improving production speed and quality.

[0072] Example 2

[0073] On the basis of Example 1, the intelligent production station screen based on face recognition technology further includes:

[0074] Worker station display screen, including: task display sub-screen and information display sub-screen;

[0075] The task display subscreen is used to display the execution task information;

[0076] The information display sub-screen is used to display the worker identity corresponding to each of the workers.

[0077] In this example, the task display subscreen and the information display subscreen are both set on the worker's workstation screen.

[0078] The working principle and beneficial effects of the above technical solution: In order to further improve the function of the workstation screen, two areas are set on the workstation screen to display different information, which is convenient for workers and managers to view.

[0079] Example 3

[0080] On the basis of Example 1, the intelligent production station screen based on face recognition technology further includes:

[0081] An information input terminal is used to collect facial organ appearance features corresponding to each facial organ dimension of a first-time employee, and establish sample identification information of the first-time employee;

[0082] The basic information of the first-time employee is collected and combined with the sample identification information to establish the worker identity of the first-time employee, and the information is transmitted to the entered information database for storage.

[0083] In this example, the identification information and worker identity of each worker in the factory have been entered into the information database.

[0084] The working principle and beneficial effects of the above technical solution: In order to facilitate uniform management, when a worker joins the company for the first time, his / her sample identification information and worker identity are collected and transmitted to the entered information database for storage, so as to facilitate the management of employees.

[0085] Example 4

[0086] On the basis of Example 1, the intelligent production station screen based on face recognition technology, the identity recognition module includes:

[0087] A picture frame correction unit is used to collect an actual facial picture frame corresponding to each of the workers, and to perform correction processing on each of the actual facial picture frames to obtain a corrected facial picture frame corresponding to each of the workers;

[0088] A facial feature matching operation unit is used to analyze the corrected facial image frame to obtain facial organ features of the corresponding worker, and to match corresponding matching identification information to each facial organ feature in the entered information database;

[0089] An identification analysis unit, used to determine whether the plurality of matching identification information corresponding to the same worker are consistent, and if consistent, to search the entered information database for the worker identity corresponding to the matching identification information;

[0090] The reorganized overall recognition unit is used to construct a facial simple group picture of the corresponding worker based on the facial organ features if the several matchable identification information corresponding to the same worker are inconsistent, and search the facial simple group picture in the entered information database to obtain the worker identity corresponding to the worker.

[0091] In this example, the actual face picture frame represents the photo of the worker at the current moment;

[0092] In this example, the correction process refers to a process of adjusting the positions of facial organs on the actual facial picture frame;

[0093] In this example, the facial organ features include: eye features, ear features, nose features, mouth features, and eyebrow features;

[0094] In this example, the matchable identification information represents sample identification information that matches a facial organ feature image;

[0095] In this example, the facial group image represents a picture frame containing only facial organs constructed according to facial organ features;

[0096] In this example, the five facial organ features may correspond to one matchable identification information or may correspond to multiple matchable identification information.

[0097] The working principle and beneficial effects of the above technical solution: In order to improve the effectiveness of face recognition and ensure the accuracy of face recognition, the actual facial picture frame of each worker is first collected and corrected to obtain a corrected facial picture frame, and then the facial organ features of the worker are determined in the corrected facial picture frame, and further a matching identification information is matched for each facial organ feature in the entered information library. If the five facial organ features correspond to the same matching identification information, then the identity of the worker can be determined. Otherwise, it can be concluded that the appearance of two or more workers is relatively similar, or the workers have put on makeup, etc. In order to avoid recognition errors, a facial simple group picture of the worker is constructed according to the facial organ features, and then the corresponding facial simple group picture is searched in the entered information library. Finally, the identity of the worker can be determined based on the search results.

[0098] Example 5

[0099] On the basis of Example 4, the intelligent production station screen based on face recognition technology, such as Figure 2 As shown, the picture frame correction unit includes:

[0100] A picture frame acquisition and mapping subunit, used for acquiring an actual facial picture frame corresponding to each of the workers, mapping the actual facial picture frame to a preset high-dimensional space to obtain a high-dimensional mapping picture frame, and mapping the actual facial picture frame to a preset low-dimensional space to obtain a low-dimensional mapping picture frame;

[0101] A high- and low-dimensional facial organ distribution determination subunit, configured to obtain a facial contour of a corresponding worker on the actual facial picture frame, obtain a high-dimensional facial organ distribution of the worker in the high-dimensional mapping picture frame, and obtain a low-dimensional facial organ distribution of the worker in the low-dimensional mapping picture frame;

[0102] An iterative correction feature extraction subunit, for performing iterative correction processing on the actual facial picture frame when the distribution features between the high-dimensional facial organ distribution and the low-dimensional facial organ distribution are inconsistent, and collecting the correction distribution features between the corresponding corrected high-dimensional facial organ distribution and the corrected low-dimensional facial organ distribution after each iterative correction processing;

[0103] The iterative correction completion processing subunit is used to stop the iterative correction processing and obtain the corresponding corrected facial image frame when the correction distribution characteristics are consistent.

[0104] In this example, the preset high-dimensional space represents a space consisting of four unknown numbers X, Y, Z and T;

[0105] In this example, the high-dimensional mapping picture frame represents a picture frame generated after mapping the actual facial picture frame into a preset high-dimensional space;

[0106] In this example, the preset low-dimensional space represents a space consisting of two unknown numbers X and Y;

[0107] In this example, in high-dimensional space, data has more features and dimensions, and can describe real-world objects and phenomena in more detail, while in low-dimensional space, data has fewer features and limited representation capabilities;

[0108] In this example, the high-dimensional facial organ distribution represents the presentation of facial organs in the facial contour in a preset high-dimensional space;

[0109] In this example, the low-dimensional facial organ distribution represents the presentation of facial organs in the facial contour in a preset low-dimensional space;

[0110] In this example, the distribution feature represents the characteristics of the positional relationship between different organs;

[0111] In this example, the iterative correction process means that the picture frame correction process is executed cyclically, and each correction result is used as the starting point of the next correction.

[0112] The working principle and beneficial effects of the above technical solution: In order to correct over-correction and achieve the purpose of correction, the actual facial picture frames collected are respectively mapped to the preset high-dimensional space and the preset low-dimensional space to obtain their corresponding high-dimensional mapping picture frames and low-dimensional mapping picture frames, and then the high-dimensional facial organ distribution and low-dimensional facial organ distribution of the workers are determined in the high-dimensional mapping picture frames and the low-dimensional mapping picture frames, and then the need for correction is judged based on the consistency of the distribution characteristics of the two facial organ distributions. If necessary, iterative processing is performed to obtain the corresponding corrected facial picture frames, thereby laying the foundation for subsequent facial analysis.

[0113] Example 6

[0114] On the basis of Example 1, the intelligent production station screen based on face recognition technology, the task issuing module includes:

[0115] An information retrieval unit, configured to retrieve historical work information, work type, and stage work goal of a corresponding worker according to the worker identity, and establish a corresponding workload of the corresponding worker in different past time periods based on the historical work information;

[0116] An efficiency analysis unit is used to retrieve a corresponding work model according to the work type, input the corresponding workload of the corresponding worker in different past time periods into the work model to simulate the historical work efficiency of the corresponding worker in each of the historical time periods, and establish a work efficiency fluctuation chart corresponding to each of the workers;

[0117] A task quantification unit is used to analyze each of the work efficiency fluctuation charts to obtain the predicted work efficiency of the corresponding worker in this time period, and generate the minimum completed task volume of the worker in this time period based on the historical work efficiency and the stage work target;

[0118] The task issuing unit is used to establish the execution task information of the corresponding worker based on the minimum completed task amount and the type of work, and transmit the execution task information to a preset display area for display.

[0119] In this example, one work type corresponds to one work model;

[0120] In this example, the stage work goal represents a work goal set by a worker before performing work;

[0121] In this example, the past time period includes several historical time periods, and one historical time period can be 8 hours;

[0122] In this example, the work efficiency fluctuation chart represents a graph showing the changes in the work efficiency of a worker in different time periods;

[0123] In this example, the time period may be 8 hours;

[0124] In this example, the guaranteed completion amount represents the minimum amount of work that the worker needs to complete within this time period.

[0125] The working principle and beneficial effects of the above technical solution: In order to provide workers with an executable and effective execution task, first retrieve the corresponding historical work information, job type and stage work goals according to the worker's identity, then retrieve the corresponding job model, and use the job model to simulate the worker's historical work efficiency corresponding to the historical time period, so as to establish the worker's work efficiency fluctuation chart, and further predict the worker's predicted work efficiency in this time period based on the work efficiency fluctuation chart, and further determine the minimum completed task volume in this time period, and finally establish the worker's execution task information in combination with the corresponding job type, and transmit it to the preset display area for the worker to view, so that it can not only provide a reference for the workers, but also allow the workers to understand their work progress.

[0126] Example 7

[0127] On the basis of Example 1, the intelligent production station screen based on face recognition technology, the supervision feedback module includes:

[0128] A data monitoring unit, used for collecting corresponding work data of each worker in different preset time periods after the worker starts working;

[0129] A finished product monitoring unit, used to analyze each of the work data to obtain the corresponding personal finished product generation amount of the corresponding worker in each preset time period;

[0130] The regional supervision unit is used to count the total finished product generation corresponding to each preset worker group in each preset time period, and to establish work feedback information of the preset worker group in combination with the individual finished product generation.

[0131] In this example, the preset time period is 1 hour;

[0132] In this example, the preset worker group refers to a processing group consisting of multiple workers that is specified in advance.

[0133] The working principle and beneficial effects of the above technical solution are as follows: by collecting the corresponding work data of workers in different preset time periods to analyze the workers' personal finished product generation and total finished product generation to establish feedback information for each worker group, so that each worker group can understand their own work efficiency and facilitate ranking after the work is completed.

[0134] Example 8

[0135] On the basis of Example 1, the intelligent production station screen based on face recognition technology, the management and adjustment module includes:

[0136] A production analysis unit is used to analyze the work feedback information to obtain the amount that can be completed by each worker group in this work cycle, retrieve the production target corresponding to each worker group, and determine the available working time and the amount of work to be done corresponding to each worker group;

[0137] A work allocation unit is used to establish the group average workload corresponding to the corresponding worker group in each work cycle according to the available working time and the workload to be done, analyze the work feedback information, and obtain the current workload corresponding to each worker in the same worker group;

[0138] A task allocation unit, configured to establish an allocation weight for each of the workers based on the order of the current workload from high to low, and to establish the corresponding allocated workload for each worker in the next work cycle based on the allocation weight and the number of workers in the corresponding worker group;

[0139] The task adjustment unit is used to adjust each of the allocated workloads according to a preset maximum allocation threshold and a minimum allocation threshold, and to establish corresponding pre-execution task information of each of the workers in the next work cycle according to the adjustment result.

[0140] In this example, the amount that can be completed represents the amount of work that a worker group can complete in this work cycle;

[0141] In this example, the group average workload represents the average workload corresponding to a group of workers;

[0142] In this example, the current workload refers to the workload completed by a worker during this work process;

[0143] In this example, the allocation weight is determined by the workload. The higher the workload, the greater the allocation weight, and the corresponding allocation workload is also greater;

[0144] In this example, the preset maximum allocation threshold is set in advance, indicating the maximum amount of tasks that a worker can perform in a work cycle;

[0145] In this example, the preset minimum allocation threshold is set in advance, indicating the minimum amount of tasks that a worker can perform in a work cycle.

[0146] The working principle and beneficial effects of the above technical solution are as follows: in order to improve management efficiency, reasonable and effective pre-execution task information is established so that workers can refer to the information for the next step of work, the amount that can be completed by each worker group is determined based on the work feedback information, and the current workload of each worker in each worker group is determined in combination with the generated goals. Further, according to the level of this workload, an allocation weight is established to determine the allocated workload corresponding to each work in the next work cycle, and finally, the allocated workload is adjusted according to the maximum allocation threshold and the minimum allocation threshold set in advance, and the pre-execution task information of the workers in the next work cycle is obtained.

[0147] Example 9

[0148] On the basis of Example 8, the intelligent production station screen based on face recognition technology, the task adjustment unit is further used for:

[0149] When each of the allocated workloads is less than the preset maximum allocated workload threshold and greater than the minimum allocated workload threshold, pre-execution task information corresponding to each of the workloads in the next work cycle will be established according to the allocated workload.

[0150] The working principle and beneficial effects of the above technical solution are as follows: when the allocated workload is reasonable, the pre-execution information is directly established according to the allocated workload, thereby improving the efficiency and speed of establishment.

[0151] Example 10

[0152] On the basis of Example 1, the intelligent production station screen based on face recognition technology, the identity recognition module is also used for:

[0153] The assessment information of the corresponding worker is generated according to the activity information of each worker in the corresponding factory, and the assessment information is transmitted to the preset display area for display.

[0154] The working principle and beneficial effects of the above technical solution are as follows: the workers' assessment information is generated, so that the workers can understand their own assessment status and adjust their work and rest schedule according to the situation.

[0155] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent production station screen based on face recognition technology, characterized in that: include: An identity recognition module, used to collect verification identification information of a worker and identify the worker identity of the corresponding worker according to the verification identification information; The identity recognition module at least includes: a picture frame correction unit, which is used to collect the actual facial picture frame corresponding to each of the workers and perform correction processing to obtain the corrected facial picture frame corresponding to each of the workers; wherein the picture frame correction unit includes: a picture frame collection and mapping subunit, which is used to collect the actual facial picture frame corresponding to each of the workers, and map the actual facial picture frame to a preset high-dimensional space and a preset low-dimensional space to obtain a high-dimensional mapping map and a low-dimensional mapping picture frame; a high- and low-dimensional facial organ distribution determination subunit, which is used to obtain the high-dimensional facial organ distribution and low-dimensional facial organ distribution of the worker in the high-dimensional mapping picture frame and the low-dimensional mapping picture frame respectively; an iterative correction feature extraction subunit, which is used to perform iterative correction processing on the actual facial picture frame, and collect the correction distribution features between the corresponding corrected high-dimensional facial organ distribution and the corrected low-dimensional facial organ distribution after each iterative correction processing; an iterative correction completion processing subunit, which is used to stop the iterative correction processing when the correction distribution features are consistent, and obtain the corresponding corrected facial picture frame; A task issuing module, used to generate corresponding task execution information based on the worker identity, and transmit the task execution information to a preset display area for display; A supervision feedback module is used to collect the work data of each worker in different preset time periods and establish work feedback information; A management adjustment module is used to adjust the pre-execution task information corresponding to each of the workers in the next work cycle based on the work feedback information.

2. The intelligent production station screen based on face recognition technology as claimed in claim 1, characterized in that: include: The worker's workstation display screen includes: a task display subscreen and an information display subscreen.

3. The intelligent production station screen based on face recognition technology as claimed in claim 1, characterized in that: include: An information input terminal is used to collect facial organ appearance features corresponding to each facial organ dimension of a first-time employee, and establish sample identification information of the first-time employee; The basic information of the first-time employee is collected and combined with the sample identification information to establish the worker identity of the first-time employee, and the information is transmitted to the entered information database for storage.

4. The intelligent production station screen based on face recognition technology as claimed in claim 1, characterized in that: The identity recognition module further includes: A facial feature matching operation unit is used to analyze the corrected facial image frame to obtain facial organ features of the corresponding worker, and to match corresponding matching identification information to each facial organ feature in the entered information database; The reorganized overall recognition unit is used to construct a facial simple group picture of the corresponding worker if the several matchable identification information corresponding to the same worker are inconsistent, and search the facial simple group picture in the entered information database to obtain the worker identity corresponding to the worker.

5. The intelligent production station screen based on face recognition technology as claimed in claim 1, characterized in that: The supervisory feedback module comprises: The regional supervision unit is used to count the total finished product generation corresponding to each preset worker group in each preset time period, and to establish work feedback information of the preset worker group in combination with the individual finished product generation.

6. The intelligent production station screen based on face recognition technology as claimed in claim 1, characterized in that: The management adjustment module includes: A production analysis unit is used to analyze the work feedback information to obtain the amount that can be completed by each worker group in this work cycle, retrieve the production target corresponding to each worker group, and determine the available working time and the amount of work to be done corresponding to each worker group; A work allocation unit is used to establish the group average workload corresponding to the corresponding worker group in each work cycle according to the available working time and the workload to be done, analyze the work feedback information, and obtain the current workload corresponding to each worker in the same worker group; A task allocation unit, configured to establish an allocation weight for each of the workers, and to establish an allocation workload corresponding to each worker in the next work cycle based on the allocation weight combined with the number of workers in the corresponding worker group; The task adjustment unit is used to adjust each of the allocated workloads according to a preset maximum allocation threshold and a minimum allocation threshold, and to establish corresponding pre-execution task information of each of the workers in the next work cycle according to the adjustment result.

7. The intelligent production station screen based on face recognition technology as claimed in claim 1, characterized in that: The identity recognition module is also used for: The assessment information of the corresponding worker is generated according to the activity information of each worker in the corresponding factory.

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