Video acquisition equipment layout optimization method and system for line monitoring

Abstract

The invention discloses a line monitoring video acquisition equipment layout optimization method and system, and belongs to the technical field of equipment layout optimization, and the method comprises the steps: generating the initial installation positions of a scene camera and a local camera, dividing a layout region into a plurality of line sections, and obtaining the influence data of each line section; integrating the line section into multiple types of sub-sections based on the influence data, and evaluating each type of sub-section to obtain an evaluation grade of the line section; screening out a complex section based on the evaluation grade, scanning the complex section to generate three-dimensional point cloud data, and constructing a three-dimensional model based on the three-dimensional point cloud data; and analyzing the three-dimensional model to obtain alternative installation positions of the plurality of cameras, and generating an optimization scheme for optimizing the positions of the scene cameras and the local cameras based on the initial installation positions and the alternative installation positions. According to the invention, the installation position optimization is carried out for the problems existing in the monitoring area, so that the monitoring effect maximization of the scene camera and the local camera is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of video surveillance, and in particular relates to a method and system for optimizing the layout of video acquisition equipment for line monitoring. Background Art

[0002] For monitoring and maintenance of high-speed rail cable lines, existing camera deployment solutions typically rely on manual experience and fixed deployment principles. This results in the camera installation locations being untargeted and unable to effectively cover key areas of the line.

[0003] In order to solve the blind spot problem in large-scale monitoring scenarios, the existing technology has proposed the following technical solutions. For example, the Chinese patent document with publication number CN116227110A discloses a multi-objective layout optimization method for road traffic facilities considering quantity constraints. Under the condition of considering quantity constraints, this method analyzes the indicators to be optimized for three alternative points: traffic congestion, traffic accidents, and traffic violations, and improves the layout density of monitoring points in the road network to achieve the task of regional blind spot control. For example, a Chinese patent document with publication number CN120105012A discloses a method and system for optimizing the layout of video observation points, which performs correlation analysis on traffic flow parameters of existing observation points, and preliminarily determines the observation points that can be transferred and the locations of new observation points based on the correlation; performs regression analysis on traffic flow parameters, fits the flow and speed of the road section, and determines the optimal fitting function; determines the extreme value positions of the flow and speed based on the optimal fitting function, and determines the road section position according to the extreme value position as the specific location of the new observation points; considers the cost and expected benefits of the new observation points, and determines the optimal layout plan for the new observation points.

[0004] However, the above technical solution is applied in urban and highway scenarios. For the maintenance of high-speed rail lines, the influence of line complexity, terrain variability, etc. needs to be considered. Therefore, the above existing technology cannot be used to solve the monitoring optimization problem in high-speed rail cable lines. Summary of the Invention

[0005] To solve the above problems, the present invention provides a method, system and storage medium for optimizing the layout of video acquisition equipment for line monitoring, so as to solve the problems existing in the above background technology.

[0006] In order to achieve the above-mentioned object of the invention, the present invention proposes a method for optimizing the layout of video acquisition equipment for line monitoring, comprising: Determine the layout area of the line and generate an initial installation plan for the cameras in the layout area. The initial installation plan includes the initial installation positions of the scene cameras and local cameras. Install cameras based on the initial installation plan, divide the deployment area into multiple line segments based on the line length and terrain data, and after an interval of a predetermined duration, obtain the impact data of each line segment. The impact data includes environmental data and line alarm data; Based on the impact data, use a clustering algorithm to integrate the line segments into multiple types of sub-segments, evaluate each type of sub-segment, and obtain the evaluation level of each line segment under the sub-segment; Based on the evaluation level, select some line segments as complex segments, scan the complex segments to generate three-dimensional point cloud data, and construct a three-dimensional model based on the three-dimensional point cloud data; Analyze the three-dimensional model to obtain alternative installation positions for multiple cameras, and generate an optimization plan for the optimized scenario cameras and the local camera positions based on the initial installation positions and the alternative installation positions.

[0007] Furthermore, analyzing the three-dimensional model to obtain alternative installation positions for multiple cameras includes the following steps: Mark multiple monitoring targets in the three-dimensional model, perform grid segmentation on the three-dimensional model to obtain multiple spatial grids, divide the spatial grids into line grids and non-line grids according to whether they belong to the components of the monitoring targets, set multiple first values based on the parameters of the scenario cameras, set generation points in the three-dimensional model, generate multiple spherical regions with the generation points as the centers and the first values as the radii, set multiple monitoring points at the boundaries of the spherical regions, locate the center points of each line grid, connect the monitoring points with the center points to obtain visible lines, and if the visible lines pass through at least one line grid, delete the visible lines; Count the total number of monitoring points including visible lines, delete the monitoring points with the total number less than the second value, obtain the occlusion rate of the cameras at the initial installation positions, if the occlusion rate is greater than the first threshold, eliminate the initial installation positions, and use the remaining monitoring points and the uneliminated initial installation positions as alternative installation positions.

[0008] Furthermore, generating an optimization plan for the scenario cameras based on the alternative installation positions includes the following steps: Set a starting value, which is the default installation quantity of the scenario cameras, and perform traversal combination on the alternative installation positions based on the starting value to obtain multiple basic installation plans; Select a basic installation plan, simulate the selected basic installation plan based on the 3D model, obtain the effective shooting values of cameras in each scenario under the basic installation plan based on the simulation results. The higher the effective shooting value, the higher the necessity of installing the scenario camera. If the distribution of the effective shooting values of the basic installation plan meets the first condition, reduce the number of scenario cameras. If the distribution of the effective shooting values meets the second condition, increase the number of scenario cameras. Repeat this step until the distribution of the effective shooting values no longer meets the first condition and the second condition. Define the basic installation plan at this time as the advanced plan; Obtain the corresponding advanced plan based on each basic installation plan, obtain the evaluation value based on the installation cost and area coverage rate of each advanced plan, and select one advanced plan as the optimized plan for the scenario camera based on the evaluation value.

[0009] Furthermore, obtaining the effective shooting values of cameras in each scenario under the basic installation plan based on the simulation results includes the following steps: Set different monitoring levels for the surfaces of each line grid based on the importance level, divide the surface of the corresponding line grid into the corresponding number of monitoring areas again based on the size of the monitoring level, determine the shooting space of each scenario camera based on the camera parameters of the scenario camera, locate the first number of monitoring areas included in the shooting space, merge the same monitoring areas in the shooting spaces of each scenario camera, record the second number of redundant monitoring areas included in each scenario camera after merging, and use the difference between the first number and the second number as the effective shooting value of the corresponding scenario camera.

[0010] Furthermore, reducing the number of scenario cameras includes the following steps: If in the basic installation plan, the number of scenario cameras with effective shooting values lower than the second threshold is greater than the first value, then the first condition is met. Start deleting the scenario cameras in sequence from the scenario camera with the smallest effective shooting value until there are more than or equal to the third number of monitoring areas that are not included in the shooting space after deletion.

[0011] Furthermore, increasing the number of scenario cameras includes the following steps: If in the basic installation plan, the number of scenario cameras with effective shooting values greater than the third threshold is less than the second value, and there are more than the third number of monitoring areas included in the shooting space, then the second condition is met. Select an empty alternative installation position in the 3D model and add a scenario camera in the selected alternative installation position. If the effective shooting value of the added scenario camera is less than the second threshold, select other alternative installation positions to add scenario cameras, and no longer use this alternative installation position as the position to add scenario cameras in the current basic installation plan.

[0012] Furthermore, generating an optimized plan for local cameras based on the alternative installation positions includes the following steps: Obtain the occlusion rate of the current local camera. If the occlusion rate is greater than the first threshold, select an alternative installation position as the replacement position, set the local camera at the replacement position, and determine its shooting angle so that the local camera continues to shoot the original area.

[0013] The present invention also provides an optimization system for arranging video acquisition devices for line monitoring. This system is used to implement the method described above. The system includes: An input module that determines the arrangement area of the line. The input module is used to generate an initial installation plan for the cameras in the arrangement area. The initial installation plan includes the initial installation positions of the scene camera and the local camera. A division module that installs cameras based on the initial installation plan. The division module divides the arrangement area into multiple line sections based on the line length and terrain data. After an interval of a predetermined time length, obtain the influence data of each line section. The influence data includes environmental data and line alarm data. An evaluation module that, based on the influence data, uses a clustering algorithm to integrate the line sections into multiple types of sub-sections, evaluates each type of sub-section, and obtains the evaluation level of each line section under the sub-section. A construction module that screens out some of the line sections as complex sections based on the evaluation level, scans the complex sections to generate three-dimensional point cloud data, and constructs a three-dimensional model based on the three-dimensional point cloud data. A generation module that is used to analyze the three-dimensional model to obtain alternative installation positions for multiple cameras, and generate an optimization plan for optimizing the positions of the scene camera and the local camera based on the initial installation position and the alternative installation positions.

[0014] The present application also provides a computer-readable storage medium. Instructions are stored on the computer-readable storage medium. When the instructions are executed by a processor, the optimization method for arranging video acquisition devices for line monitoring as described above is implemented.

[0015] Advantageous effects: Compared with the prior art, the present invention divides the arrangement area into multiple line sections, collects environmental data and alarm data, and then performs clustering analysis based on the above data, so as to classify the line sections according to similar characteristics, which is convenient for subsequent hierarchical division of the line sections, and thus efficiently screen out complex sections. Subsequently, only optimize the complex sections, which can reduce unnecessary monitoring overhead and optimize resource allocation. By constructing a three-dimensional model based on the three-dimensional point cloud data of the complex sections, the terrain of different regions can be clearly understood. On this basis, optimize the installation positions for the problems existing in the monitoring area, so as to ensure the maximization of the monitoring effects of the scene camera and the local camera, and improve the safety monitoring ability of the entire line. Description of the Drawings

[0016] Figure 1 It is a flowchart of the steps of an optimization method for the layout of video acquisition devices for line monitoring according to the present invention; Figure 2 It is a schematic diagram of the principle for determining the monitoring points according to the present invention. Detailed Embodiment

[0017] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] It can be understood that the terms "first", "second", etc. used in the present application can be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of the present application, the first xx script can be called the second xx script, and similarly, the second xx script can be called the first xx script.

[0019] As Figure 1 shown, an optimization method for the layout of video acquisition devices for line monitoring includes: S1: Determine the layout area of the line, generate an initial installation plan for the cameras in the layout area, and the initial installation plan includes the initial installation positions of the scene cameras and the local cameras.

[0020] Specifically, the layout area is the laying area of high-speed rail cables. The scene cameras are used to shoot large-range scene videos, and the local cameras are used to focus on a smaller area range to monitor some important components, such as cable joints; for the scene cameras, generally when installing the cameras, they are arranged at intervals along the cable line at a fixed distance. For example, based on the parameters of the scene cameras, a group of scene cameras are arranged at intervals of 100 m. A long-focus camera is arranged at each cable joint for monitoring. The initial installation positions of the scene cameras and the local cameras are obtained in the above manner.

[0021] S2: Determine the layout area of the line, generate an initial installation plan for the cameras in the layout area, and the initial installation plan includes the initial installation positions of the scene cameras and the local cameras.

[0022] After determining the initial installation plan, first install the cameras based on the initial installation plan. At the same time, divide the layout area into multiple line sections according to the total length of the line and the terrain data. For example, divide a line section every 1 km. After division, if a tunnel is divided into two line sections, merge the two line sections. Or if a line section contains two types of terrain information, such as including a section of tunnel and a section of mountain, then divide the line section. The ultimate purpose of merging and dividing is to make a line section include only one type of terrain. The predetermined time period is, for example, one month. After the predetermined time period, obtain the impact data of each line section. Among them, the environmental data includes temperature, wind speed, tree coverage, altitude, rainfall, etc. The higher the tree coverage, the more likely the camera is to be blocked. The line alarm data includes abnormal cable load, line fault alarm, etc.

[0023] S3: Based on the impact data, use a clustering algorithm to integrate the line sections into multiple types of sub-sections, evaluate each type of sub-section, and obtain the evaluation grade of each line section under the sub-section.

[0024] In this embodiment, the K-means clustering algorithm is used to cluster the impact data. Before clustering, the data is standardized first, and then the number of clusters is set. The number of clusters can use the elbow method. For example, after clustering, the line sections are divided into 10 types of sub-sections. For example, a certain type of sub-section includes 20 line sections. Since the impact data of the 20 line sections is similar, if one of the line sections is rated, the evaluation grades of the remaining 19 line sections can be obtained. The evaluation grade can be carried out manually. For example, set a scoring table for each data type, score the temperature, wind speed, and load according to the scoring table, and finally obtain the total score comprehensively. Determine the corresponding evaluation grade according to the value range where the total score is located.

[0025] S4: Based on the evaluation grade, select some line sections as complex sections, scan the complex sections to generate three-dimensional point cloud data, and construct a three-dimensional model based on the three-dimensional point cloud data.

[0026] The higher the evaluation grade, the more complex and changeable the environment of the line section is. Then select the line sections with larger evaluation grades as complex sections. For example, if the evaluation grades are 1-10 in total, the line sections with grades above 9 can be used as complex sections. In this way, a small number of sections can be selected from a large number of line sections as complex sections, thereby reducing the subsequent optimization cost. When generating the point cloud data, it can be obtained by means of a drone or a three-dimensional laser scanner, and then the point cloud data is converted into a three-dimensional model through CloudCompare software.

[0027] S5: Analyze the three-dimensional model to obtain alternative installation positions of multiple cameras, and generate an optimization solution for optimizing the positions of scene cameras and local cameras based on the initial installation position and the alternative installation positions.

[0028] After establishing the 3D model, first determine whether the current camera can meet the monitoring requirements at the initial installation position. For example, whether there are blind spots in the monitoring area of the scene camera, whether only one scene camera can meet the monitoring needs of the area, and whether the local camera is easily blocked during monitoring. If the above problems do not exist, there is no need to optimize the camera position.

[0029] If there are monitoring issues, multiple alternative installation locations are identified based on the 3D model. Cameras are then placed in these locations for testing to determine if the camera's coverage meets the requirements, whether blind spots are covered, or whether local cameras can capture the intended key areas. After testing, the locations and monitoring angles that meet the requirements are selected as the optimal placement, completing the camera placement optimization process.

[0030] This invention divides the deployment area into multiple line segments, collects environmental and alarm data, and then performs cluster analysis based on this data. This allows line segments to be classified by similar characteristics, facilitating subsequent hierarchical segmentation, effectively screening out complex segments. Subsequent optimization targets only these complex segments, reducing unnecessary monitoring overhead and optimizing resource allocation. By constructing a 3D model based on 3D point cloud data for complex segments, a clear understanding of the topography of different areas can be achieved. Based on this, installation locations can be optimized to address existing issues within the monitored area, maximizing the monitoring effectiveness of scene cameras and local cameras and improving the safety monitoring capabilities of the entire line.

[0031] In this embodiment, analyzing the three-dimensional model to obtain multiple candidate installation positions for cameras includes the following steps: A plurality of monitoring targets are marked in a three-dimensional model, and the three-dimensional model is gridded to obtain a plurality of spatial grids. The spatial grids are divided into line grids and non-line grids according to whether the spatial grids are components of the monitoring targets. A plurality of first values are set based on parameters of a scene camera. A generation point is set in the three-dimensional model. A plurality of spherical areas are generated with the generation point as the center and the first value as the radius. A plurality of monitoring points are set at the boundaries of the spherical areas. The center point of each line grid is located. The monitoring points are connected to the center point to obtain a visible line. If the visible line passes through at least one line grid, the visible line is deleted.

[0032] The monitoring targets include cables, cable racks, and other equipment belonging to the cable structure. Then, the 3D model is divided into grids, and the 3D model is divided into multiple cubes, namely spatial grids. The division size can be set according to actual needs, such as 0.5m * 0.5m * 0.5m. If the spatial grid belongs to the monitoring target, it is defined as a line network. Determine the shooting range of the camera according to the parameters of the scene camera. For example, if the farthest shooting distance of the scene camera is 30 meters, the first value can be set within a range less than 30 meters, such as 20 meters, 25 meters, and 30 meters. By setting multiple spherical ranges, monitoring points can be tried to be set within different ranges from the cable. For example, there is an obstacle at 29 meters. If the camera is set at 30 meters, it will be blocked by the obstacle, while setting it at 25 meters can avoid being blocked by the obstacle.

[0033] Select multiple points as generation points according to the length of the line section. For example, select a point on the cable every 40 meters in the line section as a generation point. Based on this generation point, three spherical regions are generated, and the radius of each spherical region is 20 meters, 25 meters, and 30 meters respectively. Then, multiple monitoring points are set in each spherical region.

[0034] The following introduces the process of retaining and deleting visible lines, as Figure 2 shown. For a certain spherical region, assume that monitoring points D1 to D6 are arranged along its surface. For monitoring point D1, the center point of line grid A is Z1. Connect the center point Z1 of line grid A with monitoring point D1 to obtain visible line L1. Line grid B is located directly behind line grid A. Connect the center point Z2 of line grid B with monitoring point D1 to obtain visible line L2 (not shown in the figure). Since line grid A is directly in front of line grid B, if the center point Z2 is connected with monitoring point D1 to obtain visible line L2, then visible line L2 will inevitably pass through line grid A, and then this visible line is deleted; The present invention determines the occlusion relationship according to the method of drawing visible lines. Through this method, it can be determined that line grid A can be seen from monitoring point D1 because visible line L1 does not pass through any line grid. However, when looking from D1 to monitoring point B, visible line L2 passes through line grid A, indicating that line grid A occludes line grid B. Therefore, line grid B cannot be fully seen from point D1.

[0035] Count the total number of visible lines included in each monitoring point, delete the monitoring points with a total number less than the second value, obtain the occlusion rate of the camera at the initial installation position. If the occlusion rate is greater than the first threshold, eliminate the initial installation position. The remaining monitoring points and the uneliminated initial installation positions are used as alternative installation positions.

[0036] After that, count the total number of visible lines existing in each monitoring point. If the total number decreases, it indicates that no matter how the angle of the scene camera is adjusted after being placed at this position, a good monitoring effect cannot be obtained. Therefore, it is deleted.

[0037] For the initial installation positions where cameras have been installed, calculate the probability that the camera images at these positions are blocked by foreign objects based on their historical monitoring videos. The occlusion rate can be set in the following way: Set a basic value according to a predetermined time period, for example, 100. Count the number of times the video images are blocked by foreign objects. If it is 20, then take the ratio of the number of times blocked by foreign objects to the basic value as the occlusion rate, such as 20 / 100 = 0.2. Set the first threshold to 0.1. When the occlusion rate is greater than the first threshold, eliminate this initial installation position, indicating that it is easy for foreign objects to block the camera when installed here.

[0038] The optimization scheme of the scenario cameras based on the alternative installation positions in this embodiment includes the following steps: Set a starting value, which is the default installation quantity of the scenario cameras. Based on the starting value, traverse and combine the alternative installation positions to obtain multiple basic installation schemes.

[0039] Select a basic installation scheme, simulate the selected basic installation scheme based on the 3D model, and obtain the effective shooting values of each scenario camera under the basic installation scheme based on the simulation results. The higher the effective shooting value, the higher the necessity of installing the scenario camera. If the distribution of the effective shooting values of the basic installation scheme meets the first condition, then reduce the number of scenario cameras. If the distribution of the effective shooting values meets the second condition, then increase the number of scenario cameras. Repeat this step until the distribution of the effective shooting values no longer meets the first condition and the second condition. Define the basic installation scheme at this time as the advanced scheme.

[0040] Specifically, determine the starting value according to the length of the line section and the parameters of the scenario cameras. In this embodiment, the starting value is set to 20, and then traverse and combine the alternative installation positions to obtain multiple basic installation schemes, and each basic installation scheme includes 20 scenario cameras.

[0041] After evaluating the rationality of each basic installation plan, when evaluating, according to the alternative installation locations selected by the basic installation plan, corresponding scene cameras are set in the 3D model. The shooting angle of the scene camera faces the center of the spherical area. The monitoring range is determined according to the parameters of the scene camera, and then the effective shooting value of each monitoring camera is determined according to the monitoring range. The higher the effective shooting value, the higher the necessity of installing the scene camera. When the numerical distribution of the effective shooting values of 20 scene cameras in the basic installation plan meets the first condition, for example, there are a large number of scene cameras with low effective shooting values, the number of scene cameras in the basic installation plan is reduced. If the numerical distribution of the effective shooting values meets the second condition, for example, there are a large number of scene cameras with high effective shooting values, the number of scene cameras is increased. By continuously increasing or decreasing the number of scene cameras, the rationality of the basic installation plan is continuously improved.

[0042] Based on each basic installation plan, a corresponding advanced plan is obtained. Based on the installation cost and area coverage rate of each advanced plan, an evaluation value is obtained. Based on the evaluation value, an advanced plan is selected as the optimized plan for the scene camera.

[0043] After obtaining the corresponding advanced plan according to each basic installation plan, evaluate each advanced plan to obtain the corresponding evaluation value. For example, determine the installation cost according to the number of scene cameras and the distance from the hub in the advanced plan, and determine the area coverage rate according to how many line grids are covered. If there are 100 line grids in this area and the advanced plan can monitor 95 of them, then the area coverage rate is 95 / 100 = 0.95. The installation cost and area coverage rate can be weighted and summed to obtain the evaluation value. In particular, when weighted summing, the installation cost is negative, so that the higher the calculated evaluation value, the more reasonable the advanced plan.

[0044] Specifically, the steps for obtaining the effective shooting values of each scene camera under the basic installation plan based on the simulation results in this embodiment are as follows: Set different monitoring levels for the surfaces of each line grid based on the importance level. Based on the size of the monitoring level, the surface of the corresponding line grid is further divided into the corresponding number of monitoring areas. Determine the shooting space of each scene camera based on the camera parameters of the scene camera. Locate the first number of monitoring areas including the monitoring areas in the shooting space. Merge the same monitoring areas in the shooting spaces of each scene camera, and record the second number of redundant monitoring areas included in each scene camera after merging. Take the difference between the first number and the second number as the effective shooting value of the corresponding scene camera.

[0045] For example, for the circuit grid of a cable bracket, side 1 among its six sides can reflect the cable installation situation. Therefore, side 1 is set as monitoring level 1, and the remaining sides 2 - 6 are set as monitoring level 2. Side 1 is evenly divided into two monitoring areas, and the remaining sides remain unchanged as one monitoring area.

[0046] After that, each monitoring area is numbered, and it is counted which numbered monitoring areas can be monitored by each scenario camera. For example, for scenario camera 1 at the alternative installation position 1, its conical shooting space can monitor 100 monitoring areas. The following is an example to introduce the calculation method of the effective shooting value. Suppose scenario camera 1 can monitor 100 monitoring areas, then its first quantity is 100. Similarly, scenario camera 2 can monitor 95 monitoring areas, and the first quantity is 95. Scenario camera 3 can monitor 90 monitoring areas, and the first quantity is 90. Among the monitoring areas photographed by scenario cameras 1, 2, and 3, there are 50 monitoring areas that are exactly the same. Among these 50 monitoring areas, 40 monitoring areas also exist in the shooting space of scenario camera 1. This means that among the monitoring areas photographed by scenario camera 1, 40 are also photographed by scenario camera 2 or 3. Therefore, there are 40 redundant monitoring areas for scenario camera 1, and the effective shooting value of scenario camera 1 is 100 - 40 = 60.

[0047] Based on the above, this embodiment further corrects the effective shooting value based on the following steps. Set the best monitoring direction for each monitoring target. As mentioned above, the surface of each circuit grid has a monitoring level. In the monitoring areas covered by the scenario camera, screen out the monitoring areas with a monitoring level greater than the fourth threshold as the target areas. Since the monitoring areas with a higher level are more important, the best monitoring direction must also be towards the covered monitoring areas. Take the best monitoring direction of the monitoring target as the best monitoring direction of the target area; in the shooting space of the scenario camera, vectorially combine the best monitoring directions including each target area, so as to combine multiple best monitoring directions into one vector direction, obtain the included angle between the current shooting direction of the scenario camera and the vector direction, determine the correction weight based on the size of the included angle, and multiply the correction weight by the calculated effective shooting value to complete the correction. For example, the correction weight can be obtained by performing a cosine calculation on the included angle.

[0048] In this embodiment, when reducing scenario cameras, if in the basic installation plan, the number of scenario cameras with an effective shooting value lower than the second threshold is greater than the first value, then the first condition is met. Starting from the scenario camera with the smallest effective shooting value, they are sequentially excluded until there are no less than the third quantity of monitoring areas not included in the shooting space after the exclusion.

[0049] Specifically, the second threshold is set to 30, and the first value is set to 5. When there are more than 5 effective shooting values of the scenario cameras in the basic installation plan that are less than 30, they are eliminated in order according to the size of their effective shooting values. When eliminating, it is carried out in the order of the effective shooting values from small to large. For example, if the effective shooting values of two scenario cameras are 20 and 30 respectively, the previous scenario camera is eliminated first. In addition, the third value is set to 40. If after eliminating a certain scenario camera, there are at least 40 monitoring areas in the line section that are not included in the monitoring space of any scenario camera, the elimination of cameras will no longer be carried out.

[0050] In this embodiment, increasing the number of scenario cameras includes the following steps: If in the basic installation plan, the number of scenario cameras with effective shooting values greater than the third threshold is less than the second value, and there are more than the third number of monitoring areas included in the shooting space, then the second condition is met. Select an empty alternative installation position in the 3D model and add a scenario camera in the selected alternative installation position. If the effective shooting value of the added scenario camera is less than the second threshold, select other alternative installation positions to add scenario cameras, and this alternative installation position will no longer be used as the position for adding scenario cameras in this basic installation plan.

[0051] If there are a large number of scenario cameras with large effective shooting values and there are many monitoring areas that are not monitored, it indicates that more scenario cameras can be added to expand the monitoring range. At this time, select an alternative installation position and add a scenario camera in this alternative installation position, and calculate the effective shooting value of the scenario camera; if the effective shooting value is small, it indicates that this location is not suitable for adding a camera under the layout of the current basic installation plan. At this time, select other alternative installation positions to add cameras, and when optimizing this basic installation plan later, no scenario cameras will be added here.

[0052] In this embodiment, generating an optimized plan for local cameras based on alternative installation positions includes the following steps: Obtain the occlusion rate of the current local camera. If the occlusion rate is greater than the first threshold, select an alternative installation position as the replacement position, set the local camera at the replacement position, and determine its shooting angle so that the local camera can continue to shoot the original area.

[0053] If the occlusion rate of the local camera is greater than the first threshold, select an alternative installation position that is not blocked by existing obstacles as the replacement position, install the local camera at the replacement position, and at the same time adjust its shooting angle so that the camera can continue to monitor the original area or the area near it.

[0054] In addition, the present invention also provides an optimization system for arranging video acquisition devices for line monitoring, which is used to implement the above-mentioned method. The system includes: An input module that determines the arrangement area of the line. The input module is used to generate an initial installation plan for cameras in the arrangement area, and the initial installation plan includes the initial installation positions of scene cameras and local cameras; A division module that installs cameras based on the initial installation plan. The division module divides the arrangement area into multiple line sections based on the line length and terrain data. After an interval of a predetermined duration, it obtains the influence data of each line section, and the influence data includes environmental data and line alarm data; An evaluation module that, based on the influence data, uses a clustering algorithm to integrate the line sections into multiple types of sub-sections, evaluates each type of sub-section, and obtains the evaluation level of each line section under the sub-section; A construction module that filters out some line sections as complex sections based on the evaluation level, scans the complex sections to generate three-dimensional point cloud data, and constructs a three-dimensional model based on the three-dimensional point cloud data; A generation module that is used to analyze the three-dimensional model to obtain alternative installation positions of multiple cameras, and generate an optimization plan for optimizing the positions of scene cameras and local cameras based on the initial installation positions and alternative installation positions.

[0055] The present application also provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the above-mentioned method is implemented.

[0056] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as these combinations of technical features do not conflict, they should be considered as the scope described in this specification.

[0057] The above embodiments only represent several implementation manners of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several deformations and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the invention patent should be subject to the appended claims.

[0058] The above are only the preferred embodiments of the present invention, and are not used to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An optimization method for the layout of video acquisition devices for line monitoring, characterized in that, Including: Determine the layout area of the line, generate an initial installation plan for the cameras in the layout area, and the initial installation plan includes the initial installation positions of the scene cameras and the local cameras; Install cameras based on the initial installation plan, divide the layout area into multiple line sections based on the line length and terrain data, and after an interval of a predetermined duration, obtain the impact data of each line section, where the impact data includes environmental data and line alarm data; Based on the impact data, use the clustering algorithm to integrate the line sections into various types of sub-sections, evaluate each type of sub-section, and obtain the evaluation grades of each line section under the sub-section; Select some line sections as complex sections based on the evaluation grades, scan the complex sections to generate 3D point cloud data, and construct a 3D model based on the 3D point cloud data; Analyze the 3D model to obtain alternative installation positions for multiple cameras, and generate an optimization plan for optimizing the positions of the scene cameras and the local cameras based on the initial installation positions and the alternative installation positions.

2. The optimized method for arranging video acquisition devices for line monitoring according to claim 1, wherein Analyzing the 3D model to obtain alternative installation positions for multiple cameras includes the following steps: Mark multiple monitoring targets in the 3D model, perform grid segmentation on the 3D model to obtain multiple spatial grids, divide them into line grids and non-line grids according to whether the spatial grids belong to the components of the monitoring targets, set multiple first values based on the parameters of the scene cameras, set generation points in the 3D model, generate multiple spherical regions with the generation points as the centers and the first values as the radii, set multiple monitoring points at the boundaries of the spherical regions, locate the center points of each line grid, connect the monitoring points with the center points to obtain visible lines, and if a visible line passes through at least one line grid, delete the visible line; Count the total number of visible lines including each monitoring point, delete the monitoring points with the total number less than the second value, obtain the occlusion rate of the cameras at the initial installation positions, if the occlusion rate is greater than the first threshold, eliminate the initial installation positions, and use the remaining monitoring points and the uneliminated initial installation positions as alternative installation positions.

3. The optimized method for arranging video acquisition devices for line monitoring according to claim 2, wherein Generating an optimization plan for the scene cameras based on the alternative installation positions includes the following steps: Set a starting value, where the starting value is the default installation quantity of the scene cameras, traverse and combine the alternative installation positions based on the starting value to obtain multiple basic installation plans; Select a basic installation plan, simulate the selected basic installation plan based on the 3D model, obtain the effective shooting values of each scene camera under the basic installation plan based on the simulation results, the higher the effective shooting value, the higher the installation necessity of the scene camera. If the distribution of the effective shooting values of the basic installation plan meets the first condition, reduce the number of scene cameras. If the distribution of the effective shooting values meets the second condition, increase the number of scene cameras. Repeat this step until the distribution of the effective shooting values no longer meets the first condition and the second condition, and define the basic installation plan at this time as the advanced plan; Obtain the corresponding advanced plans based on each basic installation plan, obtain the evaluation values based on the installation costs and area coverage rates of each advanced plan, and select one advanced plan as the optimization plan for the scene cameras based on the evaluation values.

4. The method for optimizing the layout of video acquisition devices for line monitoring according to claim 3, characterized in that, Obtaining the effective shooting values of cameras in each scenario under the basic installation plan based on the simulation results includes the following steps: Set different monitoring levels for the surfaces of each line grid based on the importance level. Re-divide the surface of the corresponding line grid into the corresponding number of monitoring areas based on the size of the monitoring level. Determine the shooting space of each scenario camera based on the camera parameters of the scenario camera. Locate the first quantity of monitoring areas included in the shooting space. Merge the same monitoring areas within the shooting spaces of each scenario camera. Record the second quantity of redundant monitoring areas included in each scenario camera after merging. Take the difference between the first quantity and the second quantity as the effective shooting value of the corresponding scenario camera.

5. The optimized method for arranging video acquisition devices for line monitoring according to claim 4, characterized in that, Reducing the number of scenario cameras includes the following steps: If, in the basic installation plan, the number of scenario cameras with effective shooting values lower than the second threshold is greater than the first value, then the first condition is met. Starting from the scenario camera with the smallest effective shooting value, eliminate them one by one until there are more than or equal to the third quantity of monitoring areas not included in the shooting space after elimination.

6. The method for optimizing the layout of video acquisition devices for line monitoring according to claim 5, characterized in that, Increasing the number of scenario cameras includes the following steps: If, in the basic installation plan, the number of scenario cameras with effective shooting values greater than the third threshold is less than the second value, and there are more than the third quantity of monitoring areas included in the shooting space, then the second condition is met. Select an empty alternative installation position in the 3D model and add a scenario camera at the selected alternative installation position. If the effective shooting value of the added scenario camera is less than the second threshold, select other alternative installation positions to add scenario cameras, and no longer use this alternative installation position as the position for adding scenario cameras in this basic installation plan.

7. The method for optimizing the layout of video acquisition devices for line monitoring according to claim 2, characterized in that, Generating an optimized plan for local cameras based on alternative installation positions includes the following steps: Obtain the occlusion rate of the current local camera. If the occlusion rate is greater than the first threshold, select an alternative installation position as the replacement position, set the local camera at the replacement position, and determine its shooting angle so that the local camera continues to shoot the original area.

8. A system for optimizing the layout of video acquisition devices for line monitoring, which is used to implement the method for optimizing the layout of video acquisition devices for line monitoring according to any one of claims 1-7, characterized in that, The system includes: An input module that determines the layout area of the line. The input module is used to generate an initial installation plan for the cameras in the layout area. The initial installation plan includes the initial installation positions of scenario cameras and local cameras. A division module that installs cameras based on the initial installation plan. The division module divides the layout area into multiple line sections based on the line length and terrain data. After an interval of a predetermined time duration, obtain the influence data of each line section. The influence data includes environmental data and line alarm data. An evaluation module that, based on the influence data, uses a clustering algorithm to integrate the line sections into multiple types of sub-sections, evaluates each type of sub-section, and obtains the evaluation level of each line section under the sub-section. A construction module that screens out some line sections as complex sections based on the evaluation level, scans the complex sections to generate 3D point cloud data, and constructs a 3D model based on the 3D point cloud data. A generation module that is used to analyze the 3D model to obtain alternative installation positions for multiple cameras, and generate an optimized plan for optimizing the positions of scenario cameras and local cameras based on the initial installation positions and alternative installation positions.

9. A computer-readable storage medium having instructions stored thereon, characterized in that, When the instruction is executed by a processor, it implements an optimization method for arranging a video acquisition device for line monitoring as described in any one of claims 1-7.

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