A control system based on intelligent multi-screen cooperation

Abstract

The application relates to the field of screen control, in particular to a control system based on intelligent multi-screen cooperation, which comprises a processing unit, an analysis unit, a load optimization unit and a display optimization unit. The processing unit comprises a plurality of sub-processing modules and is used for processing target videos respectively. The analysis unit is used for determining the display state of each target screen according to a picture misadjustment reference value and a display decline reference value, and determining an optimization mode as load distribution optimization or environment optimization according to a first display state proportion and a first display state aggregation degree. The load optimization unit is used for determining the screen category of the target screen according to an image complexity reference value and a dynamic reference value, and determining an optimization processing mode as task distribution optimization or task order optimization based on a balance coefficient. The display optimization unit is used for determining the environmental light influence state corresponding to each target screen according to an illumination intensity coefficient and an illumination distribution coefficient, and determining whether to adjust the brightness of the target screen according to the environmental light influence state. The application improves the display effect under the control of the multi-spliced screen.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of screen control, and in particular to a control system based on intelligent multi-screen cooperation. BACKGROUND

[0002] With the rapid development of informationization and intelligent technology, control systems are increasingly widely used in emergency management, traffic dispatching, military command and other fields. Traditional control systems usually rely on simple multi-screen expansion, and there are many problems in multi-screen environment, such as scattered key information, insufficient multi-screen cooperation capability, and unbalanced load, which seriously affect decision-making efficiency and resource utilization. Therefore, how to develop a control system based on intelligent multi-screen cooperation to improve the efficiency and intelligence of the control system in multi-screen cooperation is a technical problem that needs to be solved by those skilled in the art.

[0003] Chinese patent publication No. CN115361248A discloses a multi-screen interaction method, device and system, wherein the multi-screen interaction method comprises: establishing a communication link with a receiving terminal under the same network resource; obtaining program parameter information of a playing multimedia resource; sending the program parameter information and a play command to the receiving terminal through the communication link, so that the receiving terminal continues playing the playing multimedia resource according to the program parameter information and the play command. It can be seen that the above technical solution has the following problems: the actual resource utilization demand of each screen in the multi-screen interaction process is not considered, which easily leads to difficulty in effective allocation of processing resources, thereby affecting the multi-screen display effect. SUMMARY

[0004] Therefore, the present application provides a control system based on intelligent multi-screen cooperation to overcome the problem in the prior art that the actual resource utilization demand of each screen in the multi-screen interaction process is not considered, which easily leads to difficulty in effective allocation of processing resources, thereby affecting the multi-screen display effect.

[0005] To achieve the above-mentioned purpose, the present application provides a control system based on intelligent multi-screen cooperation, comprising:

[0006] a processing unit comprising a plurality of sub-processing modules for processing each target video;

[0007] an analysis unit connected to the processing unit for determining the display state of each target screen according to the picture misadjustment reference value and the display decline reference value, and determining the optimization mode as load distribution optimization or environment optimization according to the first display state proportion and the first display state aggregation degree;

[0008] a load optimization unit connected with the processing unit and the analysis unit respectively, configured to determine a screen category of the target screen according to the image complexity reference value and the dynamic reference value, and determine an optimization processing mode as task allocation optimization or task order optimization based on the balancing coefficient;

[0009] a display optimization unit connected with the processing unit, the analysis unit and the load optimization unit respectively, configured to determine an ambient light influence state of each target screen according to the illumination intensity coefficient and the illumination distribution coefficient, and determine whether to adjust the brightness of the target screen according to the ambient light influence state.

[0010] Further, the analysis unit determines a display state according to the picture imbalance reference value and the display decline reference value, and the display state includes:

[0011] a first display state in which the picture imbalance reference value is greater than a preset picture imbalance reference value and the display decline reference value is greater than a preset display decline reference value;

[0012] a second display state in which the picture imbalance reference value is less than or equal to the preset picture imbalance reference value or the display decline reference value is less than or equal to the preset display decline reference value.

[0013] Further, the analysis unit determines a corresponding optimization mode according to a first display state proportion and a first display state aggregation degree, and the optimization mode includes:

[0014] the optimization mode is load allocation optimization when the first display state proportion is greater than a preset first display state proportion or the first display state aggregation degree is greater than a preset aggregation degree;

[0015] the optimization mode is environment optimization when the first display state proportion is less than or equal to the preset first display state proportion and the first display state aggregation degree is less than or equal to the preset aggregation degree.

[0016] Further, when the load optimization unit performs load allocation optimization, the load optimization unit determines a screen category of each target screen according to the image complexity reference value and the dynamic reference value corresponding to each target screen, and the screen category includes:

[0017] a first category of screen in which the image complexity reference value is greater than a preset image complexity reference value and the dynamic reference value is greater than a preset dynamic reference value;

[0018] a second category of screen in which the image complexity reference value is less than or equal to the preset image complexity reference value or the dynamic reference value is less than or equal to the preset dynamic reference value.

[0019] Further, the load optimization unit detects a comparison result of the balancing coefficient and a preset balancing coefficient to determine a processing mode under a balancing analysis condition.

[0020] If the balance coefficient is greater than the preset balance coefficient, the processing manner is to optimize the task allocation;

[0021] If the balance coefficient is less than or equal to the preset balance coefficient, the processing manner is to optimize the task order;

[0022] The balance analysis condition is that the screen categories of each target screen are all determined to be completed.

[0023] Further, when the load optimization unit optimizes the task allocation, the proportion of the number of screens of one category corresponding to each target screen is detected, and the screens are arranged in descending order of the proportion of the number of screens of one category to obtain a screen sequence, and a plurality of screen combinations are obtained in the screen sequence according to a preset extraction order, and each screen combination is randomly allocated to each sub-processing module.

[0024] Further, when the load optimization unit optimizes the task order, the task analysis is performed on each sub-processing module, the correlation coefficient corresponding to each target screen corresponding to the sub-processing module is detected, and the task order priority value corresponding to the correlation coefficient is determined.

[0025] Further, when the display optimization unit optimizes the environment, the ambient light influence state corresponding to each target screen is detected, and when the ambient light influence state is that the light intensity coefficient is greater than the preset light intensity coefficient or the light distribution coefficient is greater than the preset light distribution coefficient, the target screen brightness is adjusted.

[0026] Further, when the overlapping area range is adjusted, the difference between the light intensity coefficient and the preset light intensity coefficient is recorded as the intensity difference, and the difference between the light distribution coefficient and the preset light distribution coefficient is recorded as the distribution difference.

[0027] If the intensity difference is greater than the preset intensity difference or the distribution difference is greater than the preset distribution difference, the proportion of the target screen brightness is increased;

[0028] If the intensity difference is less than or equal to the preset intensity difference and the distribution difference is less than or equal to the preset distribution difference, the fixed value of the target screen brightness is increased.

[0029] Further, each target screen includes a plurality of sub-screens.

[0030] Compared with the prior art, the beneficial effects of the present application are that, in the technical scheme of the present application, the analysis unit determines the display state of each target screen according to the picture misalignment reference value and the display decline reference value, and determines the optimization mode as load distribution optimization or environment optimization according to the first display state proportion and the first display state aggregation degree, the picture misalignment reference value and the display decline reference value reflect the quality of the video content, avoiding the problem of task conflict or load imbalance caused by improper task distribution when the prior art ignores the quality of the video content for task processing, the first display state proportion and the first display state aggregation degree reflect the task difficulty distribution degree, so that the selection of the optimization mode is more in line with the actual application scenario, thereby improving the screen display effect.

[0031] Further, in the technical scheme of the present application, the load optimization unit determines the screen category corresponding to each target screen according to the image complexity reference value and the dynamic reference value corresponding to each target screen, and the image complexity reference value and the dynamic reference value reflect the actual required resources of the target screen, and the analysis of the image complexity reference value and the dynamic reference value is helpful for the reasonable allocation of resources in the subsequent task processing process.

[0032] Further, in the technical scheme of the present application, under the balanced analysis condition, the load optimization unit determines the processing mode as task distribution optimization or task order optimization according to the comparison result of the balance coefficient and the preset balance coefficient, the balance coefficient reflects the difficulty balance degree of the current processing task of the sub-processing module, and different optimization modes are selected correspondingly, the selection of the optimization mode is beneficial to balancing the load of each sub-processing module, and is more beneficial to the analysis of task distribution, avoiding the unreasonable task distribution caused by a single optimization mode, realizing dynamic adjustment of the load of the processor, and realizing load balancing.

[0033] Further, in the technical scheme of the present application, the display optimization unit dynamically adjusts the brightness of the target screen by detecting the light intensity coefficient and the light distribution coefficient corresponding to each target screen, the light intensity coefficient and the light distribution coefficient reflect the state of the ambient light, and dynamically adjusting the brightness of the target screen is beneficial to reducing the visual impact of the ambient light on the content of the target screen.

[0034] Further, in the technical scheme of the present application, the image complexity reference value corresponding to the target screen is determined according to the image complexity corresponding to each splicing area, and the area of the splicing area is determined according to the actual situation of the target quantity reference value and the target stability reference value, so that the selection of the area of the splicing area is more accurate, and the determination accuracy of the subsequent image complexity reference value is improved. BRIEF DESCRIPTION OF DRAWINGS

[0035] Fig. 1 The unit connection diagram of the control system based on intelligent multi-screen cooperation of the present application;

[0036] Fig. 2 a flow chart for determining a display state according to a picture imbalance reference value and a display trend reference value in the present application;

[0037] Fig. 3 a flow chart for determining a screen category according to an image complexity reference value and a dynamic reference value in the picture in the present application;

[0038] Fig. 4 a flow chart for detecting a comparison result of the equalization coefficient and the preset equalization coefficient to determine a processing mode in the present application. DETAILED DESCRIPTION

[0039] In order to make the objects and advantages of the present application clearer, the present application will be further described in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0040] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood by those skilled in the art that the embodiments are only used to explain the technical principles of the present application and are not used to limit the protection scope of the present application.

[0041] It should be noted that, in the description of the present application, the terms of "upper", "lower", "left", "right", "inner", "outer" and the like indicating the direction or positional relationship are based on the direction or positional relationship shown in the drawings, which are only for the convenience of description and do not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.

[0042] In addition, it should also be noted that, in the description of the present application, unless otherwise explicitly specified and limited, the terms of "mounting", "connecting", "connection" should be understood in a broad sense, for example, can be fixed connection, can also be detachable connection, or integrally connected; can be mechanical connection, can also be electrical connection; can be directly connected, can also be indirectly connected through an intermediate medium, can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0043] Please refer to Figs. 1 to 4 As shown in the figure, the present application provides a control system based on intelligent multi-screen cooperation, comprising:

[0044] a processing unit comprising a plurality of sub-processing modules for processing each target video;

[0045] an analysis unit connected with the processing unit, for determining a display state of each target screen according to a picture imbalance reference value and a display trend reference value, and determining an optimization mode as load distribution optimization or environment optimization according to a first display state proportion and a first display state aggregation degree.

[0046] The load optimization unit, which is connected to the processing unit and the analysis unit respectively, is used to determine the screen category of the target screen based on the image complexity reference value and the dynamic reference value, and to determine the optimization processing method as task allocation optimization or task order optimization based on the balance coefficient.

[0047] The display optimization unit is connected to the processing unit, the analysis unit, and the load optimization unit, respectively. It is used to determine the ambient light influence state of each target screen based on the illuminance coefficient and the illuminance distribution coefficient, and to determine whether to adjust the brightness of the target screen based on the ambient light influence state.

[0048] This invention is applied to municipal remote command. The target video is the monitoring video of the area that needs to be monitored. The monitoring video can be obtained by fixed monitoring devices or drones. The monitoring area is the total area of ​​the area captured by the monitoring video. If drones are used, the monitoring area is the area of ​​the smallest circle on the horizontal plane that can include the projection of the drone's movement trajectory. Each sub-processing module of the processing unit has data processing capabilities to process each target video, including but not limited to image enhancement, noise reduction, color correction, and backlight compensation.

[0049] This invention utilizes historical records. Each historical record contains the following parameters during a multi-screen collaborative control process: screen misalignment reference value, display degradation reference value, first display state percentage, first display state clustering degree, image complexity reference value, dynamic reference value, equalization coefficient, ΔVt, illumination intensity coefficient, and illumination distribution coefficient. Each historical record also has a corresponding pass / fail marker. The pass / fail marker indicates whether the corresponding multi-screen collaborative control process meets the user's requirements. The pass / fail marker is manually recorded.

[0050] Specifically, the analysis unit determines the display state based on the screen misalignment reference value and the display degradation reference value. The display state includes:

[0051] The first display state is characterized by a screen misalignment reference value that is greater than the preset screen misalignment reference value and a display trend decline reference value that is greater than the preset display trend decline reference value.

[0052] The second display state is when the screen misalignment reference value is less than or equal to the preset screen misalignment reference value or the display trend decline reference value is less than or equal to the preset display trend decline reference value.

[0053] The reference value for image misalignment is denoted as V, where V is the average of the reference differences Vi corresponding to the monitoring period with the most recent preset extraction quantity.

[0054] V i =ω1C i ×ω2B i ;

[0055] wherein, i = 1, 2, 3, …, n, C i is the tearing frequency of the target screen detected in the i th monitoring period, B i is the video frame loss rate of the target screen detected in the i th monitoring period, V i is the reference difference value corresponding to the i th monitoring period, n is a preset extraction quantity; the value of the preset extraction quantity can be set by the user according to the actual application scenario; the greater the user's demand for confirmation accuracy of the picture imbalance reference value, the greater the value of the preset extraction quantity; the application has a cyclic monitoring period, and since the preset extraction quantity is n, the analysis unit determines the display state and the optimization mode once every n monitoring periods; a monitoring period and a value of a preset extraction quantity are provided, the monitoring period is 10 s, and the preset extraction quantity is 10; for a single monitoring period, the corresponding tearing frequency = the number of tears detected in the monitoring period / the length of the monitoring period; in the application, the number of tears corresponding to each monitoring period can be counted by FCAT, the video frame loss rate corresponding to a single monitoring period = the number of lost frames detected in the monitoring period / the total number of frames that should be displayed in the monitoring period, ω 1 is a first weight coefficient, ω 2 is a second weight coefficient, the values of ω 1 and ω 2 can be obtained by the user through a deep learning network and historical records; it can be understood that the greater the influence of the tearing frequency on the video display effect, the greater the value of ω 1, and the value of ω 2 has the same principle; how to obtain training samples and learn weight coefficients through historical records is easily understood by those skilled in the art, and will not be described here; a preferred value in the implementation of the application is provided, ω 1 = 0.6, and ω 2 = 0.4.

[0056] The confirmation method of the display decline reference value is to extract V i corresponding to each monitoring period, calculate ΔV t corresponding to each adjacent period, for example, ΔV 1 = V 2-V 1, ΔV 2 = V 3-V 2, ΔV t = V t+1-V t, t = 1, 2, 3, …, n-1, calculate the comparison result of each ΔV t and a preset difference value, if ΔV t is less than the preset difference value, the ΔV t is recorded as a first category difference value, if ΔV t is greater than or equal to the preset difference value, the ΔV t is recorded as a second category difference value, and the display decline reference value = the number of second category difference values / (the number of first category difference values+the number of second category difference values); the value of the preset difference value can be set by the user according to the actual application scenario; the greater the user's demand for the display effect of the target screen, the smaller the value of the preset difference value; a value is provided, the ΔV t in the historical record meeting the user's demand is counted, the outliers are removed, and the average value of the ΔV t after removing the outliers is recorded as the preset difference value.

[0057] In the present application, the screen display effect is reflected by the picture misalignment reference value, the larger the picture misalignment reference value is, the worse the display effect is, and the change degree of the picture misalignment reference value, that is, the change trend of the display effect, is represented by the display trend decline reference value, the larger the display trend decline reference value is, the change trend of the display effect is developing in a poor direction, the higher the requirement of the user for the target screen display effect is, the smaller the preset picture misalignment reference value and the preset display trend decline reference value are, the values of the preset picture misalignment reference value and the preset display trend decline reference value can be adaptively set by the user according to the actual application scene, a method for setting the values of the preset picture misalignment reference value and the preset display trend decline reference value is provided, the corresponding picture misalignment reference value and display trend decline reference value in the historical record meeting the user's demand are extracted, the abnormal values are screened out, and the average values of the picture misalignment reference value and the display trend decline reference value after screening out the abnormal values are respectively recorded as the preset picture misalignment reference value and the preset display trend decline reference value, and the screening method of the abnormal values can be but not limited to 3σ criterion method or IQR method.

[0058] Specifically, the analysis unit determines the corresponding optimization mode according to the first display state proportion and the first display state aggregation degree, and the optimization mode includes:

[0059] If the first display state proportion is greater than a preset first display state proportion or the first display state aggregation degree is greater than a preset aggregation degree, the optimization mode is load distribution optimization.

[0060] If the first display state proportion is less than or equal to the preset first display state proportion and the first display state aggregation degree is less than or equal to the preset aggregation degree, the optimization mode is environment optimization.

[0061] The first display state proportion is M1 / (M1+M2), wherein M1 is the number of target screens in the first display state detected in the latest preset extraction number of monitoring periods, and M2 is the number of target screens in the second display state detected in the latest preset extraction number of monitoring periods, the confirmation method of the first display state aggregation degree is that the time length between the first target screen in the first display state and the last target screen in the first display state in the latest preset extraction number of monitoring periods is recorded as a first time length, and the first display state aggregation degree is the first time length / the total time length of the preset extraction number of monitoring periods.

[0062] The preset first display state proportion value can be set by the user according to an actual application scene, and the first display state proportion in the application can effectively reflect the display effect of the whole target screen; the higher the requirement of the user for the display effect is, the smaller the preset first display state proportion value is; a value taking manner is provided, the first display state proportions of each monitoring period in the historical record meeting the user demand are detected, and the abnormal values are screened out, and the average value of the first display state proportions after removing the abnormal values is recorded as the preset first display state proportion; a value taking manner of the preset first display state proportion is provided, and the preset first display state proportion is 30%. The first display state aggregation degree reflects the distribution of the target screen of the first display state in time, the value of the preset first display state aggregation degree is set, the user can set the value according to the actual application scene, and the preset first display state aggregation degree can effectively reflect the influence degree of the first display state aggregation degree on the display effect in the application, therefore, the higher the requirement of the user for the display effect is, the smaller the preset first display state aggregation degree is. A value taking manner is provided, and the preset first display state aggregation degree is 0.3.

[0063] Specifically, when the load optimization unit performs load distribution optimization, the screen category corresponding to each target screen is determined according to the image complexity reference value and the dynamic reference value corresponding to each target screen, and the screen category includes:

[0064] a first type of screen with the image complexity reference value greater than a preset image complexity reference value and the dynamic reference value greater than a preset dynamic reference value;

[0065] a second type of screen with the image complexity reference value less than or equal to a preset image complexity reference value or the dynamic reference value less than or equal to a preset dynamic reference value.

[0066] In the method, for a single target screen, the image complexity corresponding to each splicing area is determined, and the average value of the image complexity is recorded as the image complexity reference value corresponding to the target screen.

[0067] The target screen in the application is spliced by several sub-screens, and the gap between any two sub-screens is called a splicing seam, which is mastered by those skilled in the art and will not be repeated. Each splicing seam of the target screen corresponds to a splicing area, the splicing area is a rectangle, the center points of the short sides of the rectangle are completely coincident with the splicing seam and have the same length, and any short side has a coincident part with the edges of the two related sub-screens of the splicing seam, and the coincident parts have the same length. The confirmation method of the area of the rectangle is to uniformly extract a plurality of basic video frames within a preset detection time of the target screen, and obtain a target quantity reference value and a target stability reference value. If the target quantity reference value is greater than a preset target quantity reference value or the target stability reference value is less than or equal to a preset target stability reference value, the areas of the rectangles of the splicing areas are the same, and the area of the rectangle and the target fluctuation degree are in a positive correlation. The target fluctuation degree is the maximum value of the target quantity difference and the target stability difference, the target quantity difference is the target quantity reference value minus the preset target quantity reference value, the target stability difference is the target stability reference value minus the preset target stability reference value, the related sub-screens are the two sub-screens corresponding to the splicing seam, and the number of basic video frames is set by the user. The greater the accuracy requirement of the user for the target quantity reference value and the target stability reference value, the greater the number of basic video frames.

[0068] If the target quantity reference value is less than or equal to the preset target quantity reference value and the target stability reference value is greater than the preset target quantity reference value, the area of the splicing area of the first splicing seam and the target fluctuation degree are in a positive correlation, and the area of the splicing area of the second splicing seam adopts the initial area.

[0069] The confirmation method of the target quantity reference value is to extract a plurality of basic video frames within a preset detection time of the target screen, and detect the target quantity of each sub-screen area in each basic video frame. c max The number of extracted basic video frames is p c The target quantity of the sub-screen in the cth basic video frame is extracted, and the target quantity of the sub-screen is the number of persons in the sub-screen.

[0070] The confirmation method of the target stability reference value is that the target stability reference value is the target quantity reference value divided by the preset detection time.

[0071] The initial area is set by the user according to the actual application scene. The higher the detection accuracy requirement of the user for the image complexity reference value, the larger the area of the sub-screen, and the larger the value of the initial area. In the specific implementation of the application, the value of the initial area is 5% of the area of the sub-screen.

[0072] The first splicing seam is a corresponding splicing seam of the target sub-screen and other sub-screens, the target sub-screen is a sub-screen whose target quantity reference value is less than or equal to a preset target quantity reference value and whose target stability reference value is greater than the preset target quantity reference value; and the second splicing seam is confirmed in a manner that other splicing seams except the first splicing seam are confirmed.

[0073] For a single splicing area, the image complexity is confirmed in a manner that a two-dimensional coordinate system is established for the splicing area, the horizontal coordinate and the vertical coordinate of a pixel block of any point of the splicing area are both greater than or equal to 0, and the image complexity is L, wherein I(x, y) is a pixel gray value at position (x, y) in the image, I0 is an average value of pixel gray values of all positions, QxW is a resolution of the image, Q is a horizontal coordinate length of the splicing area, and W is a vertical coordinate length of the splicing area.

[0074] For a single target screen, the corresponding dynamic reference value is confirmed in a manner that pixel difference values of adjacent basic video frames are calculated, the pixel difference value is an absolute value obtained by subtracting the pixel average value of each of the two basic video frames, and the average value of the pixel difference values is recorded as the dynamic reference value of the target screen.

[0075] The preset image complexity reference value and the preset dynamic reference value can be set by a user according to an actual application scenario, the preset image complexity can effectively reflect the influence degree of the color interval degree and the texture reference value on the display effect of the splicing area, the preset dynamic reference value can effectively reflect the pixel difference value of adjacent frames, a value taking manner is provided, the image complexity reference value and the dynamic reference value in the historical record meeting the user demand are counted, abnormal values are removed, and the average values of the image complexity reference value and the dynamic reference value after the abnormal values are removed are respectively recorded as the preset image complexity reference value and the preset dynamic reference value.

[0076] Specifically, the load optimization unit detects a comparison result of the balance coefficient and a preset balance coefficient under a balance analysis condition to determine a processing manner.

[0077] If the balance coefficient is greater than the preset balance coefficient, the processing manner is to optimize task allocation.

[0078] If the balance coefficient is less than or equal to the preset balance coefficient, the processing manner is to optimize task order.

[0079] The balance analysis condition is that the screen categories of all target screens are determined.

[0080] The confirmation manner of the balance coefficient is that the proportion of the number of the first type of screen corresponding to each sub-processing module is detected, the number of the processing modules whose proportion of the number of the first type of screen is greater than the preset proportion of the number of the first type of screen is detected, the number is recorded as the balance coefficient, and the preset proportion of the number of the first type of screen is 130% of the average value of the proportion of the number of the first type of screen corresponding to each processing module.

[0081] The preset balance coefficient is set by the user according to the actual display state of the target screen, and a value setting manner is provided, that is, the average value of the balance coefficient in the historical record meeting the user demand is detected and recorded as the preset balance coefficient.

[0082] Specifically, when the load optimization unit optimizes the task allocation, the proportion of the number of the first type of screen corresponding to each target screen is detected, the target screens are arranged in descending order of the proportion of the number of the first type of screen to obtain a screen sequence, and a plurality of screen combinations are obtained in the screen sequence according to a preset extraction order, and each screen combination is randomly allocated to each sub-processing module.

[0083] The preset extraction order is to extract two target screens with the largest and smallest proportion of the number of the first type of screen which are not included in the screen combination in turn, and record them as a screen combination. The number of target screens in the present application is even. If the total number of target screens in the actual application scenario is odd, the target screen with the middle value of the proportion of the number of the first type of screen is randomly allocated to any sub-processing module.

[0084] Specifically, when the load optimization unit optimizes the task sequence, the task analysis is performed on each sub-processing module, the correlation coefficients corresponding to each target screen corresponding to the sub-processing module are detected, and the task sequence priority value corresponding to the correlation coefficient is determined.

[0085] For a target screen, the other target screen corresponding to the largest correlation coefficient corresponding to the target screen is extracted. If the correlation coefficients corresponding to the two target screens are greater than the preset correlation coefficient, the task sequence priority value corresponding to the target screen with the largest image complexity reference value is equal to the image complexity reference value corresponding to the target screen + the correlation coefficient, and the task sequence priority value corresponding to the target screen with the smallest image complexity reference value is equal to - the correlation coefficient.

[0086] If the correlation coefficients corresponding to the two target screens are less than the preset correlation coefficient, the task sequence priority values corresponding to the two target screens are respectively the image complexity reference values corresponding to the two target screens. In the present application, the sub-processing module preferentially processes the target screen with a larger task sequence priority value. If there are target screens with the same task sequence priority value, a target screen is randomly selected for processing.

[0087] For two target screens, the correlation coefficient is the overlapping area of the monitoring areas corresponding to the two target screens, and the preset correlation coefficient is 40% of the average value of the monitoring areas corresponding to the two target screens.

[0088] Specifically, the display optimization unit detects the ambient light influence state corresponding to each target screen when performing environment optimization, and adjusts the target screen brightness when the ambient light influence state is that the illumination intensity coefficient is greater than the preset illumination intensity coefficient or the illumination distribution coefficient is greater than the preset illumination distribution coefficient.

[0089] When the ambient light influence state is that the illumination intensity coefficient is less than or equal to the preset illumination intensity coefficient and the illumination distribution coefficient is less than or equal to the preset illumination distribution coefficient, the target screen brightness does not need to be adjusted.

[0090] The illumination intensity coefficient is the illumination intensity in the current environment, which is detected by a luminometer and has a unit of Lux, and the illumination distribution coefficient is the area of the region where the target screen is currently illuminated,

[0091] The preset illumination intensity coefficient and the preset illumination distribution coefficient can be set by the user according to the actual application scenario. The present application can effectively reflect the illumination intensity in the environment through the illumination intensity and reflect the illumination area of the target screen through the illumination distribution coefficient. A method for setting the values of the preset illumination intensity coefficient and the preset illumination distribution coefficient is provided. The corresponding illumination intensity coefficient and illumination distribution coefficient in the historical record that meets the user's demand are extracted, the outliers are screened out, and the average values of the illumination intensity coefficient and the illumination distribution coefficient after removing the outliers are respectively recorded as the preset illumination intensity coefficient and the preset illumination distribution coefficient.

[0092] Specifically, when adjusting the overlapping area range, the difference between the illumination intensity coefficient and the preset illumination intensity coefficient is recorded as the intensity difference, and the difference between the illumination distribution coefficient and the preset illumination distribution coefficient is recorded as the distribution difference.

[0093] If the intensity difference is greater than the preset intensity difference or the distribution difference is greater than the preset distribution difference, the target screen brightness is increased by a proportion;

[0094] If the intensity difference is less than or equal to the preset intensity difference and the distribution difference is less than or equal to the preset distribution difference, the target screen brightness is increased by a fixed value.

[0095] The intensity difference = the illumination intensity coefficient - the preset illumination intensity coefficient;

[0096] The distribution difference = the illumination distribution coefficient - the preset illumination distribution coefficient;

[0097] When the target screen brightness is increased by a proportion, the increase value of the target screen brightness is positively correlated with the maximum value of the intensity difference and the distribution difference.

[0098] When the target screen brightness is increased by a fixed value, the increase value of the target screen brightness is 10% of the current target screen brightness.

[0099] In particular, each target screen comprises a number of sub-screens.

[0100] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after these changes or replacements will all fall within the protection scope of the present application.

Claims

1. A control system based on intelligent multi-screen cooperation, characterized in that, The display optimization method comprises the following steps: A processing unit comprises a plurality of sub-processing modules for processing each target video; An analysis unit is connected to the processing unit to determine the display state of each target screen according to the picture misalignment reference value and the display decline reference value, and to determine the optimization mode as load distribution optimization or environment optimization according to the first display state proportion and the first display state aggregation degree; The display state comprises a first display state in which the picture misalignment reference value is greater than a preset picture misalignment reference value and the display decline reference value is greater than a preset display decline reference value, and a second display state in which the picture misalignment reference value is less than or equal to the preset picture misalignment reference value or the display decline reference value is less than or equal to the preset display decline reference value; If the first display state proportion is greater than a preset first display state proportion or the first display state aggregation degree is greater than a preset aggregation degree, the optimization mode is load distribution optimization; If the first display state proportion is less than or equal to the preset first display state proportion and the first display state aggregation degree is less than or equal to the preset aggregation degree, the optimization mode is environment optimization; A load optimization unit is connected to the processing unit and the analysis unit to determine the screen category of each target screen according to the image complexity reference value and the dynamic reference value, and to determine the optimization processing mode as task distribution optimization or task order optimization based on the balance coefficient; A display optimization unit is connected to the processing unit, the analysis unit, and the load optimization unit to determine the environmental light influence state of each target screen according to the light intensity coefficient and the light distribution coefficient, and to determine whether to adjust the brightness of the target screen according to the environmental light influence state; When the load optimization unit performs load distribution optimization, the screen category of each target screen is determined according to the image complexity reference value and the dynamic reference value corresponding to each target screen, and the screen category comprises: a first type of screen in which the image complexity reference value is greater than a preset image complexity reference value and the dynamic reference value is greater than a preset dynamic reference value; a second type of screen in which the image complexity reference value is less than or equal to the preset image complexity reference value or the dynamic reference value is less than or equal to the preset dynamic reference value; The load optimization unit determines the processing mode under the balance analysis condition by detecting the comparison result of the balance coefficient and the preset balance coefficient; If the balance coefficient is greater than the preset balance coefficient, the processing mode is to optimize the task distribution; If the balance coefficient is less than or equal to the preset balance coefficient, the processing mode is to optimize the task order; The balance analysis condition is that the screen category of each target screen is determined.

2. The control system based on intelligent multi-screen cooperation according to claim 1, characterized in that, When the load optimization unit optimizes the task distribution, the proportion of the number of the first type of screen corresponding to each target screen is detected, the screen sequence is arranged in descending order of the proportion of the number of the first type of screen, a plurality of screen combinations are obtained in the screen sequence according to a preset extraction order, and each screen combination is randomly distributed to each sub-processing module.

3. The control system based on intelligent multi-screen cooperation according to claim 1, characterized in that, When the load optimization unit optimizes the task order, the task analysis is performed on each sub-processing module, the correlation coefficient corresponding to each target screen corresponding to the sub-processing module is detected, and the task order priority value corresponding to the sub-processing module is determined according to the correlation coefficient.

4. The control system based on intelligent multi-screen cooperation according to claim 1, characterized in that, The display optimization unit detects the ambient light influence state corresponding to each target screen when performing environment optimization, and adjusts the target screen brightness when the ambient light influence state is that the light intensity coefficient is greater than a preset light intensity coefficient or the light distribution coefficient is greater than a preset light distribution coefficient.

5. The control system based on intelligent multi-screen cooperation according to claim 4, characterized in that, When adjusting the overlapping area range, the difference between the light intensity coefficient and the preset light intensity coefficient is recorded as an intensity difference, and the difference between the light distribution coefficient and the preset light distribution coefficient is recorded as a distribution difference; If the intensity difference is greater than a preset intensity difference or the distribution difference is greater than a preset distribution difference, the proportion of the target screen brightness is increased; If the intensity difference is less than or equal to the preset intensity difference and the distribution difference is less than or equal to the preset distribution difference, the fixed value of the target screen brightness is increased.

6. The control system based on intelligent multi-screen cooperation according to claim 1, characterized in that, Each target screen includes a plurality of sub-screens.

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