Visual field determination method, construction planning method and monitoring layout planning method

Abstract

The invention provides a visual field determination method, a construction planning method and a monitoring layout planning method. The visual field determination method comprises the following steps: acquiring equipment parameters and installation parameters of image acquisition equipment; according to the equipment parameters and the installation parameters, determining obstacles influencing the collection view field of the image collection equipment and attribute information of the obstacles from a map; obtaining coordinates of the obstacle in a polar coordinate system based on the attribute information of the obstacle; wherein poles of the polar coordinate system are related to installation parameters; based on the coordinates of the obstacle in the polar coordinate system, determining a visible range of the image acquisition equipment; the visible range is an area which is not shielded by an obstacle in an acquisition view field of the image acquisition equipment. According to the invention, the efficiency of determining the visual field of the image acquisition equipment can be improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method for determining the field of view, a construction planning method, and a monitoring layout planning method. Background Technology

[0002] Surveillance equipment is widely used in security and traffic management. The deployment of surveillance equipment requires consideration of many factors, such as installation location, height, and orientation, to ensure it covers as many areas as possible and avoids significant overlap in coverage between different devices. Currently, before actual installation, the locations of surveillance equipment need to be manually determined, and the monitored areas must be tested. If the monitored areas do not meet the requirements, the equipment may need to be repeatedly removed and reinstalled in new locations for further testing. Therefore, the current deployment of surveillance equipment suffers from low efficiency. Summary of the Invention

[0003] This application provides a method for determining the field of view, a construction planning method, and a monitoring layout planning method, which can improve the efficiency of determining the field of view of image acquisition devices, thereby improving the deployment efficiency of image acquisition devices.

[0004] In a first aspect, this application provides a method for determining the field of view, the method comprising:

[0005] Obtain the device parameters and installation parameters of the image acquisition equipment;

[0006] Based on the device parameters and installation parameters, determine from the map the obstacles affecting the field of view of the image acquisition device and the attribute information of the obstacles;

[0007] Based on the attribute information of the obstacle, the coordinates of the obstacle in the polar coordinate system are obtained; wherein, the pole of the polar coordinate system is related to the installation parameters;

[0008] Based on the coordinates of the obstacle in the polar coordinate system, the field of view of the image acquisition device is determined; the field of view is the area within the field of view of the image acquisition device that is not obscured by the obstacle.

[0009] Optionally, determining the field of view of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system includes:

[0010] Based on the coordinates of the obstacle in the polar coordinate system, the coordinates of multiple target visible points in the polar coordinate system are determined; the target visible points are points that the image acquisition device can acquire.

[0011] Based on the coordinates of the multiple target visible points in the polar coordinate system, the target visible edge is obtained;

[0012] The visible field of view of the image acquisition device is determined based on the visible edge of the target.

[0013] Optionally, the coordinates of the obstacle in the polar coordinate system are the coordinates of the shape points of the obstacle in the polar coordinate system. Determining the coordinates of multiple visible target points in the polar coordinate system based on the coordinates of the obstacle includes:

[0014] Based on the coordinates of the shape points of the obstacle in the polar coordinate system, determine the equation of the straight line used to characterize the edge between different shape points;

[0015] The coordinates of the multiple visible target points in the polar coordinate system are determined using the equation of the straight line.

[0016] Optionally, determining the coordinates of the plurality of visible target points in the polar coordinate system using the equation of the straight line includes:

[0017] The coordinates of the point with the minimum radial distance among the radial distances corresponding to different angles on the linear equation are taken as the coordinates of the target visible point in the polar coordinate system; the angle is the angle between the line connecting the point on the edge represented by the linear equation and the pole and the polar axis of the polar coordinate system; the radial distance is the distance between the point on the linear equation and the pole.

[0018] Optionally, before using the coordinates of the point containing the minimum radial distance among the radial distances corresponding to different angles on the linear equation as the coordinates of the target visible point in the polar coordinate system, the method further includes:

[0019] Based on the coordinates of the shape point in the polar coordinate system, determine the angular range of the coordinates of the points on the edge represented by the equation of the straight line;

[0020] The step of using the coordinates of the point containing the minimum radial distance among the radial distances corresponding to different angles on the linear equation as the coordinates of the target visible point in the polar coordinate system includes:

[0021] Based on the radial distances corresponding to different angles within the stated angle range, the coordinates of the point where the minimum radial distance is located are used as the coordinates of the target visible point in the polar coordinate system.

[0022] Optionally, the method further includes:

[0023] Using target precision, the coordinates of the shape points of the obstacle in the polar coordinate system are truncated with precision so that the precision of the coordinates of the shape points of the obstacle in the polar coordinate system is the target precision;

[0024] Based on the target accuracy, the different angles on the equation of the line are determined.

[0025] Optionally, the installation parameters include: the coordinates of the candidate position of the image acquisition device in the initial coordinate system, the position of the pole of the polar coordinate system as the candidate position, and obtaining the coordinates of the obstacle in the polar coordinate system based on the obstacle's attribute information, including:

[0026] Transform the coordinates of the shape points of the obstacle in the initial coordinate system to the projected coordinate system to obtain the coordinates of the shape points of the obstacle in the projected coordinate system;

[0027] The coordinates of the shape points of the obstacle in the projected coordinate system are transformed to the polar coordinate system to obtain the coordinates of the shape points of the obstacle in the polar coordinate system.

[0028] Optionally, the map is used to describe the attribute information of static objects in the real world. The step of determining obstacles affecting the field of view of the image acquisition device and their attribute information from the map based on the device parameters and installation parameters includes:

[0029] Based on the device parameters and the installation parameters, the initial acquisition range of the image acquisition device is determined; the initial acquisition range is the acquisition range of the image acquisition device when there are no obstacles obstructing its field of view.

[0030] The static objects within the initial acquisition range are identified from the map as obstacles, and the attribute information of the obstacles is obtained from the map.

[0031] Optionally, the installation parameters include: candidate height of the image acquisition device, and / or candidate pitch angle. Before determining the static object within the initial acquisition range from the map as the obstacle, the method further includes:

[0032] Based on the candidate height and / or candidate pitch angle of the image acquisition device, the obstacle screening height condition is determined;

[0033] The step of determining the static objects within the initial acquisition range from the map as obstacles includes:

[0034] From the map, static objects within the initial acquisition range that meet the obstacle screening height conditions are identified as obstacles.

[0035] Optionally, the method further includes:

[0036] The visual field of the image acquisition device and the obstacles are visualized and output.

[0037] Secondly, this application provides a construction planning method, the method comprising:

[0038] The system acquires attribute information of the expected construction objects within the planned area, as well as the equipment parameters and installation parameters of the image acquisition device; the image acquisition device is used to acquire images of the planned area.

[0039] Based on the device parameters and the installation parameters, obstacles and their attribute information are determined from the expected construction targets; the obstacles are expected construction targets that affect the field of view of the image acquisition device.

[0040] Based on the attribute information of the obstacle, the coordinates of the obstacle in the polar coordinate system are obtained; wherein, the pole of the polar coordinate system is related to the installation parameters;

[0041] Based on the coordinates of the obstacle in the polar coordinate system, the field of view of the image acquisition device is determined; the field of view is the area within the field of view of the image acquisition device that is not obscured by the obstacle.

[0042] Based on the visible field, the construction planning results for the area to be planned are determined.

[0043] Thirdly, this application provides a monitoring layout planning method, the method comprising:

[0044] Obtain the equipment parameters and planned installation parameters of the image acquisition device; the image acquisition device is used to acquire images of the area where the image acquisition device is to be installed.

[0045] Based on the device parameters and the planned installation parameters, the obstacles affecting the field of view of the image acquisition device within the area and the attribute information of the obstacles are determined from the map;

[0046] Based on the attribute information of the obstacle, the coordinates of the obstacle in the polar coordinate system are obtained; wherein, the pole of the polar coordinate system is related to the installation parameters;

[0047] The field of view of the image acquisition device is determined based on the coordinates of the obstacle in the polar coordinate system.

[0048] When the visible field of view meets the preset conditions, the planned installation parameters are determined to be the target installation parameters of the image acquisition device.

[0049] Fourthly, this application provides an electronic device, including: a processor and a memory; the processor and the memory are communicatively connected.

[0050] The memory stores computer-executed instructions;

[0051] The processor executes computer execution instructions stored in the memory to implement the method as described in at least one of the first, second, and third aspects.

[0052] Fifthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in at least one of the first, second, and third aspects.

[0053] In a sixth aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in at least one of the first, second, and third aspects.

[0054] The visible field of view determination method, construction planning method, and monitoring layout planning method provided in this application can identify obstacles affecting the field of view of an image acquisition device from a map using the device's equipment and installation parameters. Then, based on the coordinates of these obstacles in a polar coordinate system, the unobstructed visible field of view of the image acquisition device can be determined. This method automates the determination of the visible field of view of an image acquisition device based on its equipment and installation parameters, eliminating the need for manual installation and thus improving the efficiency of determining the visible field of view and consequently, the deployment efficiency of the image acquisition device. Furthermore, since the coordinates of any point in a polar coordinate system are represented by the radial distance from that point to the pole and the angle between the line connecting that point and the pole and the polar axis, the visible field of view of the image acquisition device can be determined based solely on the radial distance and angle, requiring minimal computation and further improving efficiency. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 A schematic diagram of a polar coordinate system provided for this application;

[0057] Figure 2 A flowchart illustrating a method for determining the field of view provided in this application;

[0058] Figure 3 A flowchart illustrating a method for determining an obstacle and its attribute information provided in this application;

[0059] Figure 4 A schematic diagram illustrating the initial acquisition range and field of view of an image acquisition device provided in this application;

[0060] Figure 5 A flowchart illustrating a method for determining the visible field of view based on the coordinates of an obstacle in a polar coordinate system, as provided in this application;

[0061] Figure 6 A schematic diagram of the field of view of an image acquisition device in a Cartesian coordinate system provided in this application;

[0062] Figure 7 A flowchart illustrating a construction planning method provided in this application;

[0063] Figure 8 A flowchart illustrating a monitoring layout planning method provided in this application;

[0064] Figure 9 A schematic diagram of obstacles selected from a semantic map, provided for the purposes of this application;

[0065] Figure 10 A schematic diagram of a field-of-view determination device provided in this application;

[0066] Figure 11 A structural schematic diagram of a construction planning device provided in this application;

[0067] Figure 12 A schematic diagram of a monitoring layout planning device provided in this application;

[0068] Figure 13 This is a schematic diagram of the hardware structure of an electronic device provided in this application.

[0069] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0071] The following is a brief explanation of some of the terms and concepts used in this application:

[0072] Polar coordinate system: a two-dimensional coordinate system. For example, Figure 1 This is a schematic diagram of a polar coordinate system provided for this application. Figure 1 As shown, the polar coordinate system determines the position of a point on a plane using its distance from the origin (also called the pole) and its angle relative to a fixed direction. In other words, in the polar coordinate system, the position of any point P can be represented by two values: the radial distance r (radius) and the angle θ (theta). Here, r represents the distance from the pole to point P, and θ represents the angle between the line connecting point P and the pole and the positive x-axis (also called the polar axis, such as true north).

[0073] Field of view (LAV): This refers to the range of a scene that can be captured by the lens of an image acquisition device. The LAV can be two-dimensional or three-dimensional. For example, a two-dimensional LAV can be represented as a polygonal region in a two-dimensional image. Similarly, a three-dimensional LAV can be a polyhedron in three-dimensional space. Determining the LAV of an image acquisition device is crucial for fields such as photography, video recording, game development, and robot vision.

[0074] Hidden object removal: In a 2D or 3D scene, an object may be occluded by another object, causing part or all of the occluded object to become invisible. In computer graphics, the technique used to handle occlusion problems in 2D or 3D scenes is called hidden object removal. The purpose of hidden object removal algorithms is to determine which parts are visible and which parts are occluded, thereby revealing the visible parts.

[0075] High-precision oblique photogrammetry model: This is a high-precision 3D model generated by photographing ground objects from multiple angles using aerial photography equipment, and then utilizing computer vision, 3D reconstruction, and other technologies. This model can realistically reflect the shape, texture, and spatial position of ground objects, possessing high geometric accuracy and visual realism.

[0076] As mentioned earlier, the field of view is the range of the scene that the lens of an image acquisition device can capture. Therefore, it is crucial to strategically position the image acquisition device so that its field of view meets the acquisition requirements.

[0077] Taking this image acquisition device as an example of a monitoring device, the deployment of this monitoring device needs to consider many factors, such as the installation location, height, and orientation of the monitoring device, in order to ensure that it can cover as many areas as possible and ensure that there is no large amount of overlapping coverage between different monitoring devices.

[0078] Currently, before actual installation of surveillance equipment, it is necessary to manually determine the locations of the equipment and conduct on-site testing of the monitored areas. If the monitored areas do not meet the requirements, it may be necessary to repeatedly remove the surveillance equipment and try new installation locations for manual testing again. Therefore, the deployment of existing image acquisition equipment suffers from low efficiency.

[0079] The reason for the low efficiency of existing image acquisition equipment deployment is that manual placement and installation of the equipment are required to determine its field of view. This process involves repeated trial and error, leading to low efficiency. Therefore, this application proposes a method for automatically determining the field of view of an image acquisition device based on its equipment and installation parameters. This method eliminates the need for manual placement and installation, improving the efficiency of determining the field of view and thus enhancing the overall deployment efficiency of the image acquisition equipment.

[0080] Optionally, the execution entity of the field-of-view determination method provided in this application can be any electronic device with processing capabilities, such as a terminal or a server. Alternatively, the execution entity of the field-of-view determination method can be a cloud service platform, which can provide a field-of-view determination service (or field-of-view simulation service) based on the field-of-view determination method provided in any embodiment of this application.

[0081] The following describes the technical solution of this application in detail, taking an electronic device as the executing entity of the visible field determination method, with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0082] Figure 2 This is a flowchart illustrating a method for determining the field of view provided in this application. Figure 2 As shown, the method may include the following steps:

[0083] S101. Obtain the device parameters and installation parameters of the image acquisition device.

[0084] Optionally, the image acquisition device can be, for example, an apparatus for acquiring images by taking pictures and / or recording videos. Exemplarily, the image acquisition device can be any device with image acquisition capabilities, such as a camera, webcam (or surveillance equipment).

[0085] Optionally, the device parameters of an image acquisition device can refer to the shooting parameters that the image acquisition device can use or support when performing image acquisition. For example, in some embodiments, taking the image acquisition device as a camera, the device parameters can also be called camera parameters, which may include parameters such as camera model, camera focal length, and camera resolution. Taking the image acquisition device as a webcam, the camera's device parameters may include parameters such as the webcam model, focal length, and resolution.

[0086] Optionally, the installation parameters of the image acquisition device may refer to parameters that describe the expected installation result of the image acquisition device. Typically, the installation result indicated by the installation parameters of the image acquisition device can affect the field of view of the image acquisition device. For example, in some embodiments, the installation parameters may include parameters such as the expected latitude and longitude of the image acquisition device, the expected installation height, the orientation angle, and the camera pitch angle.

[0087] Optionally, the electronic device may obtain the aforementioned device parameters and installation parameters in the same or different ways. For example, taking the implementation of obtaining the aforementioned device parameters and installation parameters in the same way as an example, the electronic device may, for instance, receive the device parameters and installation parameters of the image acquisition device input by the user through an Application Programming Interface (API) or a Graphical User Interface (GUI). Alternatively, the electronic device may also obtain the device parameters and installation parameters of the image acquisition device from a pre-stored list of image acquisition device information.

[0088] Taking the different implementation methods of electronic devices obtaining the aforementioned device parameters and installation parameters as an example, for instance, the electronic device can receive the installation parameters and model number of the image acquisition device input by the user through the aforementioned API or GUI. The electronic device can then obtain the aforementioned device parameters based on the model number of the image acquisition device.

[0089] S102. Based on the equipment parameters and installation parameters, determine from the map the obstacles that affect the field of view of the image acquisition device and the attribute information of the obstacles.

[0090] The map described above can be used to describe the location and shape of static objects in the real world. For example, these static objects may include buildings, trees, bus stops, etc.

[0091] It should be understood that this application does not limit the method of map creation. For example, the map could be created based on a high-precision oblique photogrammetry model. Because high-precision oblique photogrammetry models accurately reflect the shape and spatial position of ground objects, maps created based on such models are also highly accurate, thus improving the accuracy of identifying the aforementioned obstacles and consequently improving the accuracy of subsequently determining the field of view of the image acquisition device. Alternatively, the map could be created using any existing map creation method, which will not be elaborated upon here.

[0092] Optionally, the map may be pre-stored in the electronic device. Alternatively, the map may be stored in another device, from which the electronic device can retrieve the map when needed. In some embodiments, the map may also be referred to as a semantic map.

[0093] The field of view of the aforementioned image acquisition device can refer, for example, to the spatial range that the image acquisition device can capture when there are no obstructions. If the field of view of the image acquisition device is obstructed by obstacles, the visible field of view of the image acquisition device will be smaller than the field of view. For example, the aforementioned obstacles can be static objects that affect the field of view of the image acquisition device, such as buildings, trees, urban components (e.g., bus stops, newsstands).

[0094] Optionally, the obstacle's attribute information can be used to describe its shape and spatial location. For example, the obstacle's attribute information may include the coordinates of a shape point of the obstacle. This shape point can be used to describe the shape of the obstacle. In some embodiments, the shape point can be a vertex of the obstacle. Alternatively, the obstacle's attribute information can be, for example, an identifier for the obstacle.

[0095] As one possible implementation, the electronic device can, for example, determine the field of view of the image acquisition device based on its device parameters and installation parameters. Then, the electronic device can, for example, identify objects within the field of view as obstacles from a map, and obtain the attribute information of those objects from the map as the attribute information of the obstacles.

[0096] S103. Based on the obstacle's attribute information, obtain the obstacle's coordinates in the polar coordinate system.

[0097] The pole of this polar coordinate system is related to the aforementioned installation parameters. For example, if the installation parameters include the spatial location of the image acquisition device, the spatial location of the image acquisition device could be the pole of the polar coordinate system. Optionally, the direction of the polar axis of this polar coordinate system could refer to an existing polar coordinate system, for example, the polar axis of this polar coordinate system could be due north.

[0098] Optionally, for any obstacle, the coordinates of the obstacle in the polar coordinate system can be at least one. That is, each obstacle can correspond to at least one coordinate in the polar coordinate system. For example, taking the obstacle's attribute information as including the coordinates of the obstacle's shape points as an example, the obstacle's coordinates in the polar coordinate system can be, for example, the coordinates of the obstacle's shape points in the polar coordinate system. The coordinates of the obstacle's shape points included in the attribute information can be, for example, the coordinates of the shape points in a non-polar coordinate system (such as the world coordinate system). The electronic device can, for example, transform the coordinates of the obstacle's shape points included in the attribute information to the polar coordinate system through coordinate system transformation to obtain the obstacle's coordinates in the polar coordinate system.

[0099] Alternatively, taking the obstacle's attribute information, including its identifier, as an example, the electronic device can determine the obstacle's coordinates (which can be in a non-polar coordinate system) by using the obstacle's identifier and the mapping relationship between the object's identifier and its coordinates. The mapping relationship between the object's identifier and its coordinates can, for example, be pre-stored in the electronic device. Then, the electronic device can, for example, convert the obstacle's coordinates to a polar coordinate system to obtain the obstacle's coordinates in the polar coordinate system.

[0100] S104. Based on the coordinates of the obstacle in the polar coordinate system, determine the field of view of the image acquisition device.

[0101] The aforementioned visible field of view is the area within the field of view of the image acquisition device, excluding the area obscured by obstacles, i.e., the area not obscured by the aforementioned obstacles.

[0102] As mentioned above, the coordinates of any point in the polar coordinate system are represented by the radial distance r and the angle θ, i.e., (r, θ). As one possible implementation, the electronic device can, for example, connect the coordinates of obstacles in the polar coordinate system in descending or ascending order of θ, and use the region formed by the connected contours as the field of view of the image acquisition device.

[0103] As another possible implementation, the electronic device can, for example, determine the coordinates of the points that the image acquisition device can acquire in the polar coordinate system based on the coordinates of the obstacles in the polar coordinate system, and then determine the field of view of the image acquisition device based on the coordinates of the points that the image acquisition device can acquire in the polar coordinate system.

[0104] In this embodiment, obstacles affecting the field of view of the image acquisition device can be identified from the map using the device's equipment and installation parameters. Then, based on the coordinates of these obstacles in a polar coordinate system, the unobstructed visible area of ​​the image acquisition device can be determined. This method automates the determination of the visible area of ​​the image acquisition device based on its equipment and installation parameters, eliminating the need for manual installation and thus improving the efficiency of determining the visible area and consequently, the deployment efficiency of the image acquisition device. Furthermore, since the coordinates of any point in the polar coordinate system are represented by the radial distance from that point to the pole and the angle between the line connecting that point and the pole and the polar axis, the visible area of ​​the image acquisition device can be determined based solely on the radial distance and angle, requiring minimal computation and further improving efficiency.

[0105] The following provides a detailed explanation of how electronic devices, based on their device and installation parameters, determine from a map obstacles affecting the field of view of image acquisition devices, along with the attribute information of those obstacles:

[0106] Taking the above map as an example to describe the attribute information of static objects in the real world, Figure 3 This is a flowchart illustrating a method for determining an obstacle and its attribute information, as provided in this application. Figure 3 As shown, as one possible implementation, step S102 above may include the following steps:

[0107] S201. Based on the above equipment parameters and installation parameters, determine the initial acquisition range of the image acquisition device.

[0108] The initial acquisition range can be, for example, the acquisition range of the image acquisition device when there are no obstacles obstructing its field of view. For example, Figure 4 This is a schematic diagram illustrating the initial acquisition range and field of view of an image acquisition device provided in this application. Figure 4 As shown, when an obstacle obstructs the field of view of the image acquisition device, the device will be unable to acquire images in the area obstructed by the obstacle within the initial acquisition range, while the area not obstructed by the obstacle will be the visible field of view.

[0109] For example, the electronic device determines the initial acquisition range of the image acquisition device based on the aforementioned device parameters and installation parameters. For instance, it can refer to any existing method for determining the field of view of an image acquisition device when there are no obstructions. For example, the electronic device can simulate the camera's field of view using an existing 2D camera field-of-view simulation algorithm based on the device parameters and installation parameters of the image acquisition device to be simulated. Taking the image acquisition device as a camera, for example, the existing 2D camera field-of-view simulation algorithm can, for instance, consider the ground as flat (this assumption holds true because the camera's field of view is limited). In this implementation, the 2D camera field-of-view simulation algorithm can, for instance, first determine the coordinates of the four corners of the camera image in space based on the device parameters and transform these coordinates to the world coordinate system. Then, the electronic device can, for instance, construct a rotation matrix based on the camera's pitch and yaw angles and other installation parameters. This rotation matrix is ​​used to transform points in the camera coordinate system to the world coordinate system. Through this 2D camera field-of-view simulation algorithm, the 3D coordinates can be mapped to the ground plane, and the projections of the four corner points onto the ground plane can be calculated, obtaining the polygon enclosed by the coordinates of the four corner points on the ground plane. Based on this polygon, the initial acquisition range of the camera can be obtained.

[0110] S202. Identify static objects within the initial acquisition range from the map above as obstacles, and obtain the attribute information of the obstacles from the map.

[0111] In some embodiments, the initial acquisition range can be represented by multiple location points (the area enclosed by the multiple location points is the initial acquisition range). The electronic device can, for example, determine the initial acquisition range from the map based on the multiple location points, and regard static objects within the initial acquisition range as obstacles affecting the acquisition field of view of the image acquisition device, and obtain the attribute information of the obstacles from the map.

[0112] Alternatively, in some embodiments, the electronic device may determine the aforementioned obstacles based on parameters such as candidate height and candidate pitch angle of the image acquisition device, thereby further improving the accuracy of obstacle determination.

[0113] For example, taking the aforementioned installation parameters including candidate height and / or candidate pitch angle of the image acquisition device as an example, before determining static objects within the initial acquisition range from the aforementioned map as obstacles, the electronic device may, for example, first determine the obstacle screening height condition based on the candidate height and / or candidate pitch angle of the image acquisition device. Then, the electronic device may, for example, determine from the map static objects within the initial acquisition range that meet the obstacle screening height condition as the aforementioned obstacles.

[0114] Because the field of view of an image acquisition device is related to its installation height and pitch angle, a higher candidate installation height results in a wider field of view, and static objects need to reach a higher height to become obstacles affecting the field of view. Conversely, a lower candidate installation height results in a smaller field of view, and static objects at a lower height will become obstacles affecting the field of view. Furthermore, the candidate pitch angle of the image acquisition device also affects the field of view and the selection of obstacle heights, which will not be elaborated upon here.

[0115] For example, the obstacle screening height condition mentioned above may refer to a height threshold. Optionally, the height threshold may be one height threshold or multiple height thresholds.

[0116] Taking the height threshold as an example, for instance, a static object that meets the obstacle screening height condition can refer to a static object whose height is greater than or equal to the height threshold. That is, the electronic device can, for example, determine from the map the static objects within the initial collection range whose height is greater than or equal to the height threshold, as the aforementioned obstacles. Alternatively, a static object that meets the obstacle screening height condition can refer to a static object whose height difference from the height threshold is within a preset difference range. That is, the electronic device can, for example, determine from the map the static objects within the initial collection range whose height difference from the height threshold is within a preset difference range, as the aforementioned obstacles.

[0117] Taking multiple height thresholds as an example, these multiple height thresholds can be used to determine whether static objects at different distances from the image acquisition device meet the obstacle screening height condition. For example, the height threshold for determining whether a static object meets the obstacle screening height condition can be larger for static objects farther away from the image acquisition device, and smaller for static objects closer to the image acquisition device. For any static object within the initial acquisition range of the map, the electronic device can, for example, determine that the static object meets the obstacle screening height condition when its height is greater than or equal to the height threshold corresponding to the static object, and treat the static object as an obstacle, and use the attribute information of the static object as the attribute information of the obstacle.

[0118] The above method considers the influence of the candidate height and / or candidate pitch angle of the image acquisition device on obstacle selection. The obstacle selection height condition is determined by the candidate height and / or candidate pitch angle of the image acquisition device. Based on the obstacle selection height condition, static objects within the initial acquisition range that meet the obstacle selection height condition are identified from the map as obstacles. This method realizes obstacle selection based on the candidate height and / or candidate pitch angle of the image acquisition device, improves the accuracy of obstacle selection, and further improves the accuracy of subsequent field-of-view determination based on the attribute information of the obstacle.

[0119] In this embodiment, by using device parameters and installation parameters, an initial acquisition range can be determined when there are no obstacles obstructing the field of view of the image acquisition device. Then, using this initial acquisition range, static objects within this range are identified from the map as obstacles. This method enables the identification of obstacles and their attribute information from the map based on the device parameters and installation parameters of the image acquisition device, laying the foundation for subsequently determining the visible field of view of the image acquisition device based on the obstacle's attribute information.

[0120] The following section details how electronic devices can obtain the coordinates of an obstacle in a polar coordinate system based on its attribute information:

[0121] As one possible implementation, taking the obstacle's attribute information as including: the coordinates of the obstacle's shape point in the initial coordinate system, the obstacle's coordinates in the polar coordinate system being the shape point's coordinates in the polar coordinate system, and the installation parameters including: the coordinates of the candidate position of the image acquisition device in the initial coordinate system, and the position of the pole of the polar coordinate system being the candidate position, the electronic device can, for example, transform the obstacle's shape point's coordinates in the initial coordinate system to the polar coordinate system to obtain the obstacle's shape point's coordinates in the polar coordinate system.

[0122] The coordinates of the aforementioned shape points can be used to describe the shape of the obstacle. Optionally, the number of shape points for an obstacle can be at least one. Optionally, the number of shape points for different obstacles can be the same or different.

[0123] The initial coordinate system mentioned above can be the coordinate system used when constructing the map. Optionally, the initial coordinate system can be a two-dimensional coordinate system or a three-dimensional coordinate system, and this application does not limit this. For example, the initial coordinate system can be any coordinate system other than the polar coordinate system mentioned above, such as the WGS84 coordinate system (a name for a geocentric coordinate system).

[0124] In some embodiments, the electronic device may first transform the coordinates of the shape point of the obstacle in the initial coordinate system to the projected coordinate system to obtain the coordinates of the shape point of the obstacle in the projected coordinate system. Then, the electronic device may transform the coordinates of the shape point of the obstacle in the projected coordinate system to the polar coordinate system to obtain the coordinates of the shape point of the obstacle in the polar coordinate system.

[0125] The aforementioned projection coordinate system can be used to convert three-dimensional geographic coordinates (longitude, latitude, and altitude) of the Earth's surface into two-dimensional planar coordinates. Electronic devices, for example, can use a preset projection method to project the coordinates of the shape points of an obstacle from the initial coordinate system to this projection coordinate system, thus obtaining the coordinates of the obstacle's shape points in the projection coordinate system. Different projection methods correspond to different projection coordinate systems (i.e., the coordinates in the corresponding projection coordinate systems are also different). For example, the preset projection method mentioned above could be Mercator projection or Lambert conformal conic projection, etc.

[0126] In some embodiments, before transforming the coordinates of the shape point of the obstacle in the initial coordinate system to the projected coordinate system, the electronic device may first determine the identifier of the area where the image acquisition device needs to be installed based on the installation parameters of the image acquisition device. Then, the electronic device can determine the aforementioned projected coordinate system based on the identifier of the area.

[0127] Optionally, the electronic device can also transform the coordinates of the candidate position of the image acquisition device in the initial coordinate system to the aforementioned projected coordinate system, thereby obtaining the coordinates of the candidate position in the projected coordinate system. Then, the electronic device can, for example, calculate the distance between each shape point and the candidate position in the projected coordinate system based on the coordinates of the shape points and the candidate positions, as the value of the radial distance r of the shape point in the polar coordinate system. The electronic device can also calculate the angle between the line connecting the shape point and the candidate position and the polar axis direction (e.g., due north) based on the coordinates of the shape points and the candidate positions, as the value of the angle θ of the shape point in the polar coordinate system, thereby obtaining the coordinates (r, θ) of each shape point in the polar coordinate system.

[0128] In this embodiment, the coordinates of the shape points of the obstacle in the initial coordinate system are first transformed to the projected coordinate system. This realizes the projection of the shape points of the obstacle into a planar coordinate system, that is, the position of the shape points of the obstacle is represented by the coordinates in the same plane. This simplifies the representation of the coordinates of the shape points of the obstacle and improves the efficiency of calculating the coordinates of the shape points of the obstacle in the polar coordinate system based on the coordinates of the shape points of the obstacle in the projected coordinate system. In other words, it further improves the efficiency of determining the visible field based on the coordinates of the shape points of the obstacle in the polar coordinate system.

[0129] The following section provides a detailed explanation of how electronic devices determine the field of view of the aforementioned image acquisition device based on the coordinates of the obstacle in the polar coordinate system:

[0130] Figure 5 This is a flowchart illustrating a method for determining the visible field of view based on the coordinates of an obstacle in a polar coordinate system, as provided in this application. Figure 5 As shown, as one possible implementation, the aforementioned step S104 may include, for example, the following steps:

[0131] S301. Based on the coordinates of the obstacles in the polar coordinate system, determine the coordinates of multiple visible target points in the polar coordinate system.

[0132] The aforementioned visible target points are the points that the image acquisition device can acquire, or in other words, the points that it can capture.

[0133] In some embodiments, taking the coordinates of the obstacle in the polar coordinate system as the coordinates of the shape point in the polar coordinate system as an example (the attribute information of the obstacle includes the coordinates of the shape point of the obstacle in the initial coordinate system, which can be referred to in the foregoing embodiments and will not be repeated here), the electronic device can, for example, determine the coordinates of the above-mentioned multiple target visible points in the polar coordinate system based on the coordinates of the shape point of the obstacle in the polar coordinate system.

[0134] For example, an electronic device can determine the equation of a straight line representing the edge between different shape points based on the coordinates of the shape points of the obstacle in a polar coordinate system. Then, the electronic device can use this straight line equation to determine the coordinates of the aforementioned multiple visible target points in a polar coordinate system.

[0135] The aforementioned points of different shapes can refer, for example, to points of different shapes within the same obstacle, and / or to points of different shapes within different obstacles. The edges between these points of different shapes can be between any two points of different shapes within the same obstacle, or between two points of different shapes belonging to two different obstacles.

[0136] Optionally, the electronic device determines the above-mentioned straight line equation in a manner that, for example, can refer to existing methods for determining the equation of a straight line passing through two points based on their coordinates. For instance, the electronic device can, for example, determine the straight line equation passing through any two shape points (which may belong to the same obstacle or different obstacles) from all shape points of obstacles affecting the field of view of the image acquisition device, based on the coordinates of these two shape points in a polar coordinate system. In some embodiments, taking the electronic device obtaining multiple above-mentioned straight line equations based on the coordinates of the shape points of the obstacle in a polar coordinate system as an example, these multiple straight line equations can also be referred to as a system of straight line equations.

[0137] As mentioned earlier, the coordinates of a point in the polar coordinate system are (r, θ), meaning the coordinates of all points on the aforementioned linear equation are (r, θ), i.e., (radial distance, angle). Here, the radial distance is the distance between the point on the linear equation and the pole. The angle is the angle between the line connecting the point on the linear equation and the polar axis of the polar coordinate system. Therefore, in some embodiments, the electronic device can, for example, use the coordinates of the point with the smallest radial distance among the radial distances corresponding to different angles on the aforementioned linear equation as the coordinates of the target's visible point in the polar coordinate system.

[0138] It should be understood that this application does not limit how the electronic device calculates the coordinates of the point containing the minimum radial distance among the radial distances corresponding to different angles on the linear equation. For example, taking the electronic device as an example, based on the coordinates of the shape point of the obstacle in the polar coordinate system, multiple linear equations are obtained, and these multiple linear equations are called a system of linear equations. In order to reduce the computational load of determining the coordinates of the visible point of the target in the polar coordinate system, the coordinates of the visible point of the target in the polar coordinate system can be obtained, for example, through matrix calculation.

[0139] For example, an electronic device can calculate the obstacle edge coefficient matrix C by using the coordinates of the obstacle shape points in the polar coordinate system. The shape of the coefficient matrix C is [N edge ,2]. Wherein, N edge This represents the number of linear equations. The coefficient matrix C can, for example, satisfy the following formula (1):

[0140] D=CΘ (1)

[0141] Where Θ represents the "different angles" mentioned in "different angles corresponding to radial distances on the equation of a straight line". Matrix D has the shape [N] prec N edge ] represents the distance matrix of Θ on each line in the system of linear equations, N precThis represents the number of the aforementioned "different angles". In the polar coordinate system, the problem of determining the visible point of the target is simplified to finding the minimum value, avoiding the high computational cost of pairwise comparisons.

[0142] The following is an illustrative example of how an electronic device determines the specific angle values ​​corresponding to "different angles" on the above linear equation:

[0143] In some embodiments, since the coordinates of a point in the aforementioned polar coordinate system are (radial distance, angle), the angle values ​​specifically corresponding to "different angles" on the aforementioned linear equation can, for example, be related to the precision of the coordinates in the polar coordinate system. For instance, before using the coordinates of the point containing the minimum radial distance among the radial distances corresponding to different angles on the aforementioned linear equation as the coordinates of the target visible point in the polar coordinate system, the electronic device can, for example, first use a target precision to truncate the coordinates of the obstacle's shape points in the polar coordinate system, ensuring that the precision of the obstacle's shape points' coordinates in the polar coordinate system is the target precision. The electronic device can also determine the different angles on the aforementioned linear equation based on this target precision.

[0144] For example, the target precision can be pre-stored in the electronic device. This target precision can be, for example, one or two decimal places. The electronic device can, for example, use this target precision to retain one or two decimal places of the shape point's coordinates in the polar coordinate system, thereby truncating the coordinates of the shape point in the polar coordinate system to achieve a target precision, such that the coordinates of the obstacle's shape point in the polar coordinate system retain one or two decimal places.

[0145] Optionally, the more precise the target accuracy, that is, the more decimal places the coordinates of the shape points in the polar coordinate system retain, the more different angles the aforementioned straight line equation can correspond to. For example, assuming the target accuracy is one decimal place, since the angle range in the polar coordinate system is (0, 2π), after retaining one decimal place, the angle range becomes (0, 6.2). In this example, the different angles corresponding to the aforementioned straight line equation can be, for example, 7 different angles: 0, 1, 2, 3, 4, 5, and 6.

[0146] Therefore, precision truncation does not affect the spatial relationship between shape points. By using the aforementioned target precision, the coordinates of the shape points of the obstacle in the polar coordinate system are precisely truncated. This ensures the accuracy of the coordinates of the visible target points in the polar coordinate system while reducing the complexity of the coordinate representation, thus further reducing the computational load and improving the computational efficiency of calculating the coordinates of the visible target points in the polar coordinate system based on the coordinates of the shape points in the polar coordinate system. Furthermore, the aforementioned target precision can also be used for different angles corresponding to the aforementioned straight line equation, laying the foundation for determining the coordinates of the visible target points in the polar coordinate system based on the radial distances corresponding to different angles on the straight line equation.

[0147] In some embodiments, before using the coordinates of the point with the smallest radial distance among the radial distances corresponding to different angles on the above-mentioned straight line equation as the coordinates of the target visible point in the polar coordinate system, the electronic device may, for example, first determine the angular range of the coordinates of the points on the edge represented by the straight line equation.

[0148] For example, an electronic device can determine the angular range of coordinates of points on the edge represented by the equation of a straight line based on the coordinates of the shape points in the polar coordinate system. Then, the electronic device can use the coordinates of the point containing the minimum radial distance among the radial distances corresponding to the different angles within that angular range on the equation of the straight line as the coordinates of the target's visible point in the polar coordinate system.

[0149] For example, using this straight line equation as the equation representing the edge between shape point 1 (r1, θ1) and shape point 2 (r2, θ2), the electronic device can, for example, determine the angle range corresponding to this straight line equation based on θ1 and θ2. Assuming θ1 < θ2, the electronic device can, for example, determine the angle range corresponding to this straight line equation as [θ1, θ2]. Alternatively, the electronic device can, for example, determine the angle range corresponding to this straight line equation as [θ1 - θ0, θ2 + θ0]. Here, θ0 can, for example, be an angle pre-stored in the electronic device.

[0150] The above method enables electronic devices to determine the coordinates of a target visible point in the polar coordinate system within the angle range corresponding to the straight line equation determined based on the coordinates of the shape point in the polar coordinate system. This reduces the amount of computation required to determine the coordinates of the target visible point in the polar coordinate system, further improving the efficiency of determining the coordinates of the target visible point in the polar coordinate system. Therefore, it improves the efficiency of subsequently determining the visible field of view based on the coordinates of the target visible point in the polar coordinate system.

[0151] In some embodiments, the electronic device may also use the aforementioned initial acquisition range to eliminate the coordinates of the target visible points in the polar coordinate system determined by the method described in any of the foregoing embodiments. For example, the electronic device may first transform the initial acquisition range to the polar coordinate system to obtain the initial acquisition range represented by coordinates in the polar coordinate system. Then, the electronic device may retain the target visible points "within the initial acquisition range" and perform subsequent operations to obtain the target visible edge based on the coordinates of the target visible points in the polar coordinate system. Alternatively, the electronic device may delete the target visible points "outside the initial acquisition range" to ensure that the visible field of view determined based on the target visible points is within the initial acquisition range, further improving the accuracy of the visible field of view.

[0152] S302. Based on the coordinates of multiple target visible points in the polar coordinate system, obtain the target visible edge.

[0153] Optionally, the visible edge of the target is used to constitute the field of view of the image acquisition device.

[0154] In some embodiments, the aforementioned target visible edge can be a target visible edge determined in a coordinate system other than the polar coordinate system. This non-polar coordinate system (hereinafter referred to as the target coordinate system) can be, for example, the aforementioned initial coordinate system or a user-specified coordinate system. The electronic device can, for example, first transform the coordinates of multiple target visible points in the polar coordinate system to the target coordinate system to obtain the coordinates of the multiple target visible points in the target coordinate system. Then, the electronic device can sequentially connect the multiple target visible points based on their coordinates in the target coordinate system to obtain the aforementioned target visible edge.

[0155] S303. Determine the field of view of the image acquisition device based on the visible edge of the target.

[0156] For example, taking the target coordinate system as a Cartesian coordinate system (such as the aforementioned projected coordinate system), the electronic device can first transform the coordinates of multiple visible target points in the polar coordinate system to the Cartesian coordinate system, obtaining the coordinates of the multiple visible target points in the Cartesian coordinate system. Then, based on the coordinates of the multiple visible target points in the Cartesian coordinate system, the multiple visible target points are sequentially connected to obtain the aforementioned visible target edge. For example, Figure 6 This is a schematic diagram illustrating the field of view of an image acquisition device in a Cartesian coordinate system, as provided in this application. Figure 6 As shown, x1, x2, x3, x4, and x5 are the x-axis coordinates of the Cartesian coordinate system, and y1, y2, y3, and y4 are the y-axis coordinates of the Cartesian coordinate system.

[0157] In some embodiments, the aforementioned target visibility edge can be, for example, obtained by connecting the coordinates of the target visibility point in the polar coordinate system in ascending order of angles. That is, the target visibility edge can be a target visibility edge determined in the polar coordinate system.

[0158] In this embodiment, by using the coordinates of the obstacle in the polar coordinate system, the coordinates of the target visible point that the image acquisition device can acquire in the polar coordinate system can be determined. Furthermore, based on the coordinates of this target visible point in the polar coordinate system, the target visible edge constituting the field of view of the image acquisition device can be determined. Through this method, the field of view of the image acquisition device is determined based on the coordinates of the obstacle in the polar coordinate system, achieving automated field of view determination without requiring manual placement and installation of the image acquisition device, thus improving the efficiency of determining the field of view of the image acquisition device.

[0159] As one possible implementation, after determining the field of view of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system, the electronic device can, for example, visualize the field of view of the image acquisition device and the aforementioned obstacle.

[0160] For example, the visualization output may include: rendering the field of view of the image acquisition device and the aforementioned obstacles to obtain an image including the field of view and the aforementioned obstacles, and outputting the image.

[0161] By using the above method, the field of view of the image acquisition device and the aforementioned obstacles are visualized and output, allowing users to view the field of view and the obstacles affecting the acquisition field of view of the image acquisition device. This enables users to know the field of view of the image acquisition device under the installation parameters and the obstacles that cause the field of view, providing users with a reference for the layout of the image acquisition device, avoiding the need for manual actual placement and installation of the image acquisition device, and improving the deployment efficiency of the image acquisition device.

[0162] Alternatively, after determining the field of view of the image acquisition device, the electronic device can, for example, fuse the field of view of each image acquisition device in the target area based on the field of view of other image acquisition devices in the target area and the field of view of the current image acquisition device, to obtain an overall field of view corresponding to all image acquisition devices in the target area. Then, the electronic device can, for example, compare this overall field of view with the target area to determine whether the overall field of view can completely cover the target area. If so, the electronic device can, for example, output a layout result of the image acquisition devices for the target area. This layout result may, for example, include the installation parameters and device parameters of each image acquisition device in the target area.

[0163] Alternatively, if the overall field of view fails to completely cover the target area, the electronic device may, for example, output a prompt message to the user to re-enter the device parameters and installation parameters of a new image acquisition device. Based on the new device parameters and installation parameters, and referring to the field of view determination method described in any of the foregoing embodiments, the field of view simulation is re-performed to determine whether the new overall field of view can completely cover the target area. Alternatively, the electronic device may, for example, when it is determined that the overall field of view fails to completely cover the target area, regenerate the device parameters and installation parameters of a new image acquisition device according to a preset algorithm. Based on the new device parameters and installation parameters, and referring to the field of view determination method described in any of the foregoing embodiments, the field of view simulation is re-performed to determine whether the new overall field of view can completely cover the target area. The preset algorithm may, for example, first determine, based on the overall field of view and the target area, that the overall field of view fails to cover the area to be covered within the target area. Then, based on the location of the area to be covered, the device parameters and installation parameters of the new image acquisition device are generated.

[0164] It should be understood that this application does not limit the application scenarios of the field of view determination method. For example, the field of view determination method of any embodiment of this application can be used in fields such as urban construction planning and surveillance layout planning. The following uses urban construction planning and surveillance layout planning as examples to illustrate the application scenarios of this field of view determination method:

[0165] As one possible implementation method, Figure 7 This is a flowchart illustrating a construction planning method provided in this application. Figure 7 As shown, the method may include the following steps:

[0166] S401. Obtain the attribute information of the expected construction objects in the area to be planned, as well as the equipment parameters and installation parameters of the image acquisition device.

[0167] The image acquisition device can be used to acquire images of the area to be planned. The intended construction objects within the planned area can be, for example, static objects in the map described in any of the foregoing embodiments. The attribute information of the intended construction objects can be referenced from the attribute information of static objects in the map described in any of the foregoing embodiments. The image acquisition device can be any of the image acquisition devices described in the foregoing embodiments, and will not be elaborated further here.

[0168] S402. Based on equipment parameters and installation parameters, determine the obstacles and their attribute information from the expected construction objects.

[0169] The obstacle is a planned construction object that affects the field of view of the image acquisition device. Optionally, the electronic device determines the implementation method of the obstacle from the planned construction object based on the device parameters and installation parameters. For example, it can refer to the method described in any of the foregoing embodiments for determining the obstacle affecting the field of view of the image acquisition device and the attribute information of the obstacle from the map based on the device parameters and installation parameters, which will not be elaborated here.

[0170] S403. Based on the obstacle's attribute information, obtain the obstacle's coordinates in the polar coordinate system.

[0171] The poles of this polar coordinate system are related to the installation parameters.

[0172] S404. Determine the field of view of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system.

[0173] The visible field of view is the area within the field of view of the image acquisition device that is not obstructed by obstacles.

[0174] Optionally, step S403 can be implemented in the same way as step S103, and step S404 can be implemented in the same way as step S104, which will not be repeated here.

[0175] S405. Based on the visible field, determine the construction planning results for the area to be planned.

[0176] The aforementioned construction planning results may include, for example, suggested installation locations for image acquisition equipment in the area to be planned, and attribute information of expected construction objects that have a significant impact on the field of view of the image acquisition equipment.

[0177] For example, an electronic device may calculate the size of the visible field of view, the size of the overlapping area of ​​the visible fields of view between different image acquisition devices, and then, based on the size of the visible field of view, the size of the overlapping area of ​​the visible fields of view between different image acquisition devices, determine whether the device parameters and installation parameters of the image acquisition device meet the preset conditions for the coverage area of ​​the image acquisition device.

[0178] For example, the preset conditions may include: the area of ​​the visible field of view is greater than or equal to a first preset area, and the area of ​​the overlapping region of the visible fields of view between adjacent image acquisition devices is less than or equal to a second preset area. The electronic device, for example, can determine that the device parameters and installation parameters of the image acquisition device meet the preset conditions for the coverage area of ​​the image acquisition device when the area of ​​the visible field of view is greater than or equal to the first preset area and the area of ​​the overlapping region of the visible fields of view between adjacent image acquisition devices is less than or equal to the second preset area. If satisfied, the electronic device can output a construction planning result including the device parameters and installation parameters of the image acquisition device.

[0179] For example, the electronic device may determine that the device parameters and installation parameters of the image acquisition device do not meet the preset conditions for the coverage area of ​​the image acquisition device when the area of ​​the visible field of view is less than a first preset area, and / or the area of ​​the overlapping region of the visible fields of adjacent image acquisition devices is greater than a second preset area. Optionally, the electronic device may output a prompt message indicating that the device parameters and installation parameters of the image acquisition device do not meet the preset conditions for the coverage area of ​​the image acquisition device.

[0180] In this embodiment, based on the attribute information of the expected construction objects within the planned area and the equipment parameters and installation parameters of the image acquisition device, obstacles can be identified from the expected construction objects. Then, based on the coordinates of the obstacles in the polar coordinate system, the unobstructed field of view of the image acquisition device can be determined. This method automates the determination of the field of view of the image acquisition device based on its equipment parameters and installation parameters, eliminating the need for manual installation and placement of the device. This improves the efficiency of determining the field of view and consequently, the efficiency of obtaining the construction planning results for the planned area based on this field of view. Furthermore, since the coordinates of any point in the polar coordinate system are represented by the radial distance from the point to the pole and the angle between the line connecting the point and the pole and the polar axis, the field of view of the image acquisition device can be determined based solely on the radial distance and angle. This requires minimal computation, further improving the efficiency of determining the field of view and obtaining the construction planning results for the planned area.

[0181] As one possible implementation method, Figure 8 This is a flowchart illustrating a monitoring layout planning method provided in this application. Figure 8 As shown, the method may include the following steps:

[0182] S501. Obtain the equipment parameters and planned installation parameters of the image acquisition device.

[0183] The image acquisition device is used to acquire images of the area where the image acquisition device is to be deployed. The planning and installation parameters can refer to the installation parameters described in the foregoing embodiments. For example, the planning and installation parameters may include at least one of the following: the latitude and longitude, altitude, pitch angle, and yaw angle at which the image acquisition device can be installed.

[0184] S502. Based on equipment parameters, planned installation parameters, and the map, determine the obstacles and their attribute information that affect the field of view of the image acquisition equipment in the above-mentioned area.

[0185] S503. Based on the obstacle's attribute information, obtain the obstacle's coordinates in the polar coordinate system.

[0186] The poles of the polar coordinate system are related to the installation parameters.

[0187] S504. Determine the field of view of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system.

[0188] Among them, the above optional steps S502 can refer to the implementation of S102, S503 can refer to the implementation of S103, and S504 can refer to the implementation of S104, which will not be repeated here.

[0189] S505. When it is determined that the above-mentioned field of view meets the preset conditions, the above-mentioned planned installation parameters are determined as the target installation parameters of the image acquisition device.

[0190] The aforementioned target installation parameters can be used to indicate that the image acquisition device can be installed according to the target installation parameters, and the achieved field of view can meet the needs of image acquisition of the area where the image acquisition device is to be laid out.

[0191] For example, the preset condition may include: the area of ​​the visible field is greater than or equal to a preset visible field area. Optionally, after acquiring the visible field, the electronic device may, for example, calculate the area of ​​the visible field and compare it with the size of the preset visible field area. If the area of ​​the visible field of the image acquisition device is greater than or equal to the preset visible field area, i.e., the visible field meets the preset condition, the electronic device may use the planning installation parameters obtained in step S501 as the target installation parameters. Alternatively, if the area of ​​the visible field of the image acquisition device is less than the preset visible field area, i.e., the visible field does not meet the preset condition, indicating that the planning installation parameters do not meet the requirements for image acquisition of the area where the image acquisition device is to be laid out, the electronic device may, for example, adjust the planning installation parameters based on a preset adjustment algorithm to obtain the adjusted planning installation parameters. Then, the electronic device can, for example, re-execute the aforementioned operation of determining the visible field based on the adjusted planning and installation parameters to obtain the re-determined visible field, and determine whether the area of ​​the re-determined visible field is greater than or equal to the preset visible field area, until it is determined that the area of ​​the visible field of the image acquisition device is greater than or equal to the preset visible field area, and then use the planning and installation parameters as the aforementioned target installation parameters.

[0192] For example, the aforementioned preset adjustment algorithm can be used to adjust the planning and installation parameters according to a preset adjustment step size for each parameter in the planning and installation parameters, thereby obtaining the adjusted planning and installation parameters. For example, taking the planning and installation parameters including the latitude and longitude, altitude, pitch angle, and yaw angle where the image acquisition device can be installed as an example, the preset adjustment step size corresponding to different parameters can be different. For example, the preset adjustment step size corresponding to latitude and longitude can be a preset length shifted to the left (or right), the preset adjustment step size corresponding to altitude can be a preset altitude adjustment (or a preset altitude adjustment), and the preset adjustment step size corresponding to pitch angle and yaw angle can be a preset angle adjustment in a preset direction.

[0193] Alternatively, if the visible area of ​​the aforementioned image acquisition device is smaller than the preset visible area, i.e., it is determined that the visible area does not meet the preset conditions, the electronic device may output a prompt message indicating that "the monitoring layout planning based on the device parameters and planned installation parameters of the image acquisition device is unreasonable."

[0194] In this embodiment, for the area where an image acquisition device is to be deployed, obstacles can be identified from the area based on the device parameters and installation parameters of the image acquisition device. Then, based on the coordinates of the obstacles in the polar coordinate system, the unobstructed field of view of the image acquisition device can be determined. This method automates the determination of the field of view of the image acquisition device based on its device parameters and installation parameters, eliminating the need for manual installation of the device in the area. This improves the efficiency of determining the field of view and, consequently, the efficiency of determining the target installation parameters based on that field of view. Furthermore, since the coordinates of any point in the polar coordinate system are represented by the radial distance from the point to the pole and the angle between the line connecting the point and the pole and the polar axis, the field of view of the image acquisition device can be determined based solely on the radial distance and angle. This requires less computation, further improving the efficiency of determining the field of view and obtaining the target installation parameters of the image acquisition device in the area where it is to be deployed.

[0195] The following example illustrates the method for determining the field of view provided in this application.

[0196] In some embodiments, the field-of-view determination method provided in this application may include, for example, the following steps:

[0197] First, it receives user input of device parameters, the location and orientation of the pole where the camera is to be installed, and other parameters.

[0198] Equipment parameters may include, for example, camera model, camera focal length, camera resolution, and other parameters that affect the camera's shooting range.

[0199] For example, electronic devices can receive parameters such as the latitude and longitude of the pole (i.e., the latitude and longitude of the camera), height, target orientation angle, and camera pitch angle input by the user, in order to determine the position and orientation of the camera (i.e., the aforementioned image acquisition device) in space.

[0200] Then, the electronic device calls the field of view determination algorithm (or simulation algorithm) proposed in this application to obtain and filter obstacles from the semantic map and perform polar coordinate transformation. Then, the obstacle culling algorithm proposed in this application determines the field of view of the camera.

[0201] For example, a method for filtering obstacles can be described as follows:

[0202] First, the electronic device can determine the initial acquisition range of the image acquisition device when there are no obstructions blocking its field of view. For example, based on the input device parameters to be simulated, existing 2D camera field of view simulation algorithms can be used to simulate the camera's field of view. For instance, these existing algorithms may assume the ground is flat, an assumption that is generally true due to the limited field of view of the camera. The electronic device can determine the coordinates of the four corners of the camera frame in space and transform these coordinates to the world coordinate system. Then, a rotation matrix can be constructed based on the camera's pitch and yaw angles. The rotation matrix is ​​used to transform points in the camera coordinate system to the world coordinate system. Then, the 3D coordinates are mapped to the ground plane, and the projections of the four corner points onto the ground plane are calculated. Finally, the polygon enclosed by the coordinates of the four corner points on the ground plane can be returned.

[0203] Then, the electronic device can identify static objects within the initial acquisition range as obstacles from the semantic map and obtain the attribute information of the obstacles from the map. Specifically, the electronic device can acquire the semantic map from a high-precision oblique photogrammetry model. The high-precision oblique photogrammetry model can recreate the positions of static objects in the real physical world on a one-to-one scale, and the semantic map acquired based on this model can faithfully reproduce the real world. Compared with traditional orthophotogrammetry, oblique photogrammetry can acquire multi-view information of three-dimensional objects such as buildings, thus more accurately representing their shape and structure in the 3D model. Simultaneously, due to the use of high-resolution cameras and advanced image processing algorithms, the high-precision oblique photogrammetry model has stronger detail representation capabilities, clearly displaying the surface texture and minute features of ground objects. The semantic map acquisition method can be automatically identified through existing implementation methods such as manual annotation or machine learning algorithms, which will not be elaborated here. This semantic map M can be represented as a set of N spatial polyhedra M = {O0, O1, ..., O...} n-1}

[0204] For example, Figure 9 This is a schematic diagram illustrating obstacles selected from a semantic map, as provided in this application. Figure 9 As shown, the black polygons represent obstacles. For example, obstacles may include trees, buildings, urban components (newsstands, bus stops), and other objects that may affect the camera's field of view.

[0205] For example, an obstacle removal algorithm can be described as follows:

[0206] First, the electronic device can convert the coordinates of the shape points of the obstacles (or the set of obstacles) in the initial coordinate system, the above-mentioned installation parameters Θ={ξ,α,β}, and the initial acquisition range (or the unhidden two-dimensional field of view V) to the polar coordinate system.

[0207] Where ξ = {longitude, latitude, altitude} represents the camera's position in the WGS84 coordinate system, α represents the camera's orientation angle relative to true north in the WGS84 coordinate system (true north is 0 degrees, true south is 180 degrees), and β represents the camera's pitch angle relative to the ground plane (0 degrees horizontally relative to the ground plane, 90 degrees vertically relative to the ground). The unhidden area of ​​view in two dimensions is V = [v0, v1, ..., v m-1 ξ is a polygon with m vertices in the WGS84 coordinate system. Each point has the same structure as ξ, including longitude, latitude, and altitude. The obstacle set M = {O0, O1, ..., O...} n-1} is a set of n obstacles, each of which is a polygon in the WGS84 coordinate system and has the same structure as the two-dimensional visible field.

[0208] A coordinate system transformation is performed on the camera's latitude and longitude ξ, the vertices of the 2D visible field V, and the vertices (shape points) of all obstacles M. For example, the transformation is first performed to a projected coordinate system. For instance, this projected coordinate system could be the Cartesian coordinate system EPSG 32651. EPSG 32651 is a code for a projected coordinate system belonging to UTM zone 51N, where UTM (Universal Transverse Mercator) is a universal transverse Mercator projection. If the image acquisition device is used to acquire data from areas outside UTM 51N, the projected coordinate system can be changed to the corresponding area to ensure the accuracy of the coordinates in the projected coordinate system.

[0209] Then, a polar coordinate system transformation can be performed. In this polar coordinate system, the origin is the camera position ξ, θ represents the angle between point p and true north, and d represents the Euclidean distance d from point p to ξ. In some embodiments, the height of each point may not be used in the calculation process and is maintained through transmission until output for application use. After the polar coordinate transformation, the spatial relationship between obstacles is preserved, and the occlusion relationship between obstacles is equivalent to the distance relationship between obstacles on the x-coordinate. Therefore, the first intersection point of the rays emanating outward from each angle value with the obstacle can be calculated; this intersection point is the farthest point in the visible field of view.

[0210] As mentioned earlier, before determining the coordinates of the target's visible points, the angle values ​​of the coordinate points in the transformed polar coordinate system can be truncated to improve computational efficiency. Since precision truncation does not affect the spatial relationships between points, it improves computational efficiency without compromising application performance. For example, precision truncation can retain K decimal places for all coordinate values. K is an adjustable parameter value. Users can adjust it according to their precision requirements to meet different application needs.

[0211] Then, based on the coordinates of the obstacle in the polar coordinate system, the coordinates of the visible vertex of the obstacle (i.e. the visible point of the target mentioned above) are calculated.

[0212] As mentioned above, in the polar coordinate system, determining the boundary of the visible field after hidden surface removal can be transformed into determining the first intersection point (the point with the smallest d) between the rays emanating outward from each angle value (i.e., the perpendicular line of the horizontal coordinate angle) and the obstacle. Considering that in real-world scenarios, obstacles often occlude each other or partially occlude due to differences in size, this application considers the visibility of vertices and the visibility of points on the edges between vertices. For example, the process of determining the above-mentioned target visible point can be obtained through matrix calculation to improve computational efficiency, for example, referring to the aforementioned formula (1). After determining the coordinates of the target visible point in the polar coordinate system, the visible polygonal region can be obtained by connecting the points in order of the horizontal coordinate values. Then, the electronic device can convert the visible polygonal region back to the Cartesian coordinate system to obtain the visible field and output it.

[0213] Compared to existing hidden surface removal algorithms, such as the Z-Buffer Algorithm (which maintains a depth value, or Z-value, for each pixel. When a new pixel is to be drawn, its depth value is compared with the value in the Z-buffer; if the new pixel is closer to the observer, the old pixel is replaced. This algorithm requires additional memory to store the Z-buffer), Painter's Algorithm (a depth-sorting method that first sorts all polygons according to their distance from the observer, then draws them sequentially starting with the farthest polygon; however, this algorithm cannot handle complex overlaps between objects correctly), and Splitting Algorithms (such as the Binary Space Partitioning Tree, which handles the hidden surface removal problem by recursively splitting the scene into two halves, incurring high preprocessing costs when building the BSP tree), all of the above-mentioned existing hidden surface removal algorithms require a graphics processing unit (GPU). Even with high computing power (such as a computer, GPU) or other high-performance computing or additional storage, it is not directly applicable to the hidden surface removal problem in two-dimensional scenes. The hidden surface removal algorithm provided in this application can perform hidden surface removal in two-dimensional visible fields, and reduces the amount of computation for hidden surface removal, thereby improving the efficiency of hidden surface removal computation.

[0214] Finally, the simulation results, including the visible field, will be output.

[0215] For example, simulation results may also include information such as camera resolution, the location and size of obstacles.

[0216] In this embodiment, a semantic map is obtained from a high-precision oblique photogrammetry model. Since the high-precision oblique photogrammetry model can reproduce the positions of static objects in the real physical world on a one-to-one basis, the semantic map obtained based on this model can faithfully reproduce the real world, thus improving the accuracy of obstacle screening based on this semantic map. By converting to a polar coordinate system for the execution of the hidden surface removal algorithm, the accuracy and efficiency of the simulation results (i.e., determining the visible field of view) are improved. The simulation results are output for users to view and evaluate the camera's visible field of view. This method can be applied, for example, to urban construction planning, surveillance camera layout planning, etc., to verify the camera installation effect in advance, improve design and planning efficiency, and reduce the cost of manual trial and error.

[0217] Figure 10 This is a schematic diagram of a field-of-view determination device provided in this application. Figure 10 As shown, the field-of-view determination device may include: an acquisition module 51 and a processing module 52. Wherein,

[0218] The acquisition module 51 is used to acquire the device parameters and installation parameters of the image acquisition device.

[0219] Processing module 52 is configured to, based on the device parameters and installation parameters, determine from the map obstacles affecting the field of view of the image acquisition device and the attribute information of the obstacles; obtain the coordinates of the obstacles in a polar coordinate system based on the attribute information of the obstacles; and determine the visible field of view of the image acquisition device based on the coordinates of the obstacles in the polar coordinate system. The pole of the polar coordinate system is related to the installation parameters; the visible field of view is the area within the field of view of the image acquisition device that is not obscured by the obstacles.

[0220] Optionally, the processing module 52 is specifically configured to: determine the coordinates of multiple target visible points in the polar coordinate system based on the coordinates of the obstacle in the polar coordinate system; obtain a target visible edge based on the coordinates of the multiple target visible points in the polar coordinate system; and determine the field of view of the image acquisition device based on the target visible edge. Wherein, the target visible points are points that the image acquisition device can acquire.

[0221] Taking the attribute information of the obstacle as including: the coordinates of the shape point of the obstacle in the initial coordinate system, and the coordinates of the obstacle in the polar coordinate system as the coordinates of the shape point in the polar coordinate system, optionally, the processing module 52 is specifically used to determine the straight line equation for representing the edge between different shape points based on the coordinates of the shape point of the obstacle in the polar coordinate system; and to determine the coordinates of the multiple target visible points in the polar coordinate system through the straight line equation.

[0222] Optionally, the processing module 52 is specifically used to take the coordinates of the point where the minimum radial distance is located among the radial distances corresponding to different angles on the linear equation as the coordinates of the target visible point in the polar coordinate system. Here, the angle is the angle between the line connecting the point on the edge represented by the linear equation and the pole, and the polar axis of the polar coordinate system; the radial distance is the distance between the point on the linear equation and the pole.

[0223] Optionally, processing module 52 is further configured to, before using the coordinates of the point containing the minimum radial distance among the radial distances corresponding to different angles on the linear equation as the coordinates of the target visible point in the polar coordinate system, determine the angular range of the coordinates of the points on the edge represented by the linear equation based on the coordinates of the shape point in the polar coordinate system. Specifically, processing module 52 is configured to use the coordinates of the point containing the minimum radial distance among the radial distances corresponding to different angles within the angular range on the linear equation as the coordinates of the target visible point in the polar coordinate system.

[0224] Optionally, the processing module 52 is further configured to, before using the coordinates of the point where the minimum radial distance is located among the radial distances corresponding to different angles on the linear equation as the coordinates of the target visible point in the polar coordinate system, use a target precision to truncate the coordinates of the shape points of the obstacle in the polar coordinate system so that the precision of the coordinates of the shape points of the obstacle in the polar coordinate system is the target precision; and determine the different angles on the linear equation based on the target precision.

[0225] Taking the installation parameters including the coordinates of the candidate position of the image acquisition device in the initial coordinate system and the position of the pole of the polar coordinate system as the candidate position, optionally, the processing module 52 is specifically used to transform the coordinates of the shape points of the obstacle in the initial coordinate system to the projected coordinate system to obtain the coordinates of the shape points of the obstacle in the projected coordinate system; and transform the coordinates of the shape points of the obstacle in the projected coordinate system to the polar coordinate system to obtain the coordinates of the shape points of the obstacle in the polar coordinate system.

[0226] The map is used to describe the attribute information of static objects in the real world. Optionally, the processing module 52 is specifically used to determine the initial acquisition range of the image acquisition device based on the device parameters and the installation parameters; to identify the static objects within the initial acquisition range from the map as obstacles, and to obtain the attribute information of the obstacles from the map. The initial acquisition range is the acquisition range of the image acquisition device when there are no obstacles obstructing its field of view.

[0227] Taking the installation parameters including the candidate height and / or candidate pitch angle of the image acquisition device as an example, optionally, the processing module 52 is further configured to determine obstacle screening height conditions based on the candidate height and / or candidate pitch angle of the image acquisition device before determining the static object within the initial acquisition range from the map as the obstacle. Optionally, the processing module 52 is specifically configured to determine, from the map, static objects within the initial acquisition range that satisfy the obstacle screening height conditions as the obstacle.

[0228] Optionally, the field of view determination device may further include an output module 53, which is used to visualize the field of view of the image acquisition device and the obstacle after determining the field of view of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system.

[0229] The field of view determination device provided in this application is used to execute the aforementioned field of view determination method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0230] Figure 11 A structural schematic diagram of a construction planning device provided for this application. (See attached diagram.) Figure 11 As shown, the construction planning device may include: an acquisition module 61, a processing module 62, and a determination module 63.

[0231] The acquisition module 61 is used to acquire attribute information of the expected construction objects within the area to be planned, as well as the device parameters and installation parameters of the image acquisition device. The image acquisition device is used to acquire images of the area to be planned.

[0232] Processing module 62 is configured to: determine obstacles and their attribute information from the expected construction objects based on the device parameters and the installation parameters; obtain the coordinates of the obstacles in a polar coordinate system based on the obstacle attribute information; and determine the field of view of the image acquisition device based on the coordinates of the obstacles in the polar coordinate system. Wherein, the obstacle is the expected construction object that affects the field of view of the image acquisition device; the pole of the polar coordinate system is related to the installation parameters; and the field of view is the area within the field of view of the image acquisition device that is not obstructed by the obstacle.

[0233] The determination module 63 is used to determine the construction planning result of the area to be planned based on the visible field.

[0234] The construction planning device provided in this application is used to execute the aforementioned construction planning method embodiments. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0235] Figure 12 This is a structural schematic diagram of a monitoring layout planning device provided in this application. Figure 12 As shown, the monitoring layout planning device may include: an acquisition module 71, a processing module 72, and a determination module 73.

[0236] The acquisition module 71 is used to acquire the device parameters and planned installation parameters of the image acquisition device. The image acquisition device is used to acquire images of the area where it is to be installed.

[0237] Processing module 72 is configured to, based on the device parameters, the planned installation parameters, and from the map, determine obstacles within the area that affect the field of view of the image acquisition device and their attribute information; based on the obstacle attribute information, obtain the coordinates of the obstacles in a polar coordinate system; and based on the coordinates of the obstacles in the polar coordinate system, determine the visible field of view of the image acquisition device. The pole of the polar coordinate system is related to the installation parameters.

[0238] The determination module 73 is used to determine the planned installation parameters as the target installation parameters of the image acquisition device when it is determined that the visible field meets the preset conditions.

[0239] The monitoring layout planning device provided in this application is used to execute the aforementioned monitoring layout planning method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0240] Figure 13 This is a schematic diagram of the hardware structure of an electronic device provided in this application. Figure 13 The illustrated electronic device 80 includes a memory 81, a processor 82, and a communication interface 83. The memory 81, processor 82, and communication interface 83 are communicatively connected to each other. For example, the memory 81, processor 82, and communication interface 83 can be connected via a network. Alternatively, the electronic device 80 may also include a bus 84. The memory 81, processor 82, and communication interface 83 are communicatively connected to each other via the bus 84. Figure 13 It is an electronic device 80 in which the memory 81, processor 82, and communication interface 83 are connected to each other via bus 84.

[0241] The memory 81 may be a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 81 may store a program, and when the program stored in the memory 81 is executed by the processor 82, the processor 82 and the communication interface 83 are used to execute at least one method of field-of-view determination, construction planning, and monitoring layout planning as described in any of the foregoing embodiments. The memory may also store data required for at least one method of field-of-view determination, construction planning, and monitoring layout planning.

[0242] The processor 82 can be a general-purpose CPU, microprocessor, application-specific integrated circuit (ASIC), graphics processing unit (GPU), or one or more integrated circuits.

[0243] The processor 82 can also be an integrated circuit chip with signal processing capabilities. In implementation, at least one method in the field-of-view determination, construction planning, and monitoring layout planning of this application can be completed by the integrated logic circuits in the hardware of the processor 82 or by instructions in software form. The aforementioned processor 82 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments below of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments below of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 81. Processor 82 reads the information in memory 81 and, in conjunction with its hardware, completes the road information processing of this application.

[0244] The communication interface 83 uses transceiver modules, such as, but not limited to, transceivers, to enable communication between the electronic device 80 and other devices or communication networks. For example, a dataset can be acquired through the communication interface 83.

[0245] When the aforementioned electronic device 80 includes a bus 84, the bus 84 may include a path for transmitting information between various components of the electronic device 80 (e.g., memory 81, processor 82, communication interface 83).

[0246] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used in the methods described in the above embodiments.

[0247] This application also provides a program product including executable instructions stored in a readable storage medium. At least one processor of an electronic device can read the executable instructions from the readable storage medium, and the processor executes the executable instructions to cause the electronic device to implement at least one of the methods for field-of-view determination, construction planning, and monitoring layout planning provided in the various embodiments described above.

[0248] The term "multiple" in this document refers to two or more. The term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the preceding and following related objects; in formulas, " / " indicates a "division" relationship. Additionally, it should be understood that in the description of this application, words such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0249] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application.

[0250] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A visual field determination method, characterized by, The method comprises: obtaining device parameters and installation parameters of an image acquisition device; determining, from a map, an obstacle affecting a collection field of view of the image acquisition device and attribute information of the obstacle according to the device parameters and the installation parameters; obtaining coordinates of the obstacle in a polar coordinate system based on the attribute information of the obstacle; wherein a pole of the polar coordinate system is related to the installation parameters; determining a visible domain of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system; the visible domain is a region in the collection field of view of the image acquisition device that is not blocked by the obstacle.

2. The method of claim 1, wherein, The determination of the visible domain of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system comprises: determining coordinates of a plurality of target visible points in the polar coordinate system based on the coordinates of the obstacle in the polar coordinate system; the target visible points are points that can be collected by the image acquisition device; obtaining a target visible edge based on the coordinates of the plurality of target visible points in the polar coordinate system; determining the visible domain of the image acquisition device based on the target visible edge.

3. The method of claim 2, wherein, The coordinates of the obstacle in the polar coordinate system are coordinates of shape points of the obstacle in the polar coordinate system, and the determination of the coordinates of the plurality of target visible points in the polar coordinate system based on the coordinates of the obstacle in the polar coordinate system comprises: determining a straight line equation for representing edges between different shape points based on the coordinates of the shape points of the obstacle in the polar coordinate system; determining the coordinates of the plurality of target visible points in the polar coordinate system through the straight line equation.

4. The method of claim 3, wherein, The determination of the coordinates of the plurality of target visible points in the polar coordinate system through the straight line equation comprises: taking coordinates of a point with a minimum radial distance corresponding to different angles on the straight line equation as the coordinates of the target visible point in the polar coordinate system; the angle is an included angle between a line connecting a point on the edge represented by the straight line equation and the pole and a polar axis of the polar coordinate system; and the radial distance is a distance between the point on the straight line equation and the pole.

5. The method of claim 4, wherein, Before the taking of the coordinates of the point with the minimum radial distance corresponding to different angles on the straight line equation as the coordinates of the target visible point in the polar coordinate system, the method further comprises: determining an angle range of the coordinates of the point on the edge represented by the straight line equation based on the coordinates of the shape points in the polar coordinate system; The taking of the coordinates of the point with the minimum radial distance corresponding to different angles on the straight line equation as the coordinates of the target visible point in the polar coordinate system comprises: taking, as the coordinates of the target visible point in the polar coordinate system, coordinates of a point with a minimum radial distance corresponding to different angles within the angle range.

6. The method according to claim 4 or 5, characterized in that, The method further comprises: performing precision truncation on the coordinates of the shape points of the obstacle in the polar coordinate system using a target precision, so that the precision of the coordinates of the shape points of the obstacle in the polar coordinate system is the target precision. Determine the different angles on the straight line equation based on the target accuracy.

7. The method according to any one of claims 3-5, characterized in that, The installation parameters include coordinates of a candidate position of the image acquisition device in an initial coordinate system, and a position of a pole point of the polar coordinate system is the candidate position, and the attribute information of the obstacle is obtained based on the attribute information of the obstacle, and the obtaining the coordinates of the obstacle in the polar coordinate system comprises: Converting the coordinates of the shape points of the obstacle in the initial coordinate system to a projection coordinate system to obtain the coordinates of the shape points of the obstacle in the projection coordinate system; Converting the coordinates of the shape points of the obstacle in the projection coordinate system to the polar coordinate system to obtain the coordinates of the shape points of the obstacle in the polar coordinate system.

8. The method according to any one of claims 1 to 5, characterized in that, The map is used to describe attribute information of static objects in a real world, and the determining the obstacle affecting a collection field of view of the image acquisition device and the attribute information of the obstacle from the map based on the device parameters and the installation parameters comprises: Determining an initial collection range of the image acquisition device based on the device parameters and the installation parameters; the initial collection range is a collection range of the image acquisition device when there is no obstacle to block the collection field of view of the image acquisition device; Determining the static objects in the initial collection range from the map as the obstacle, and obtaining the attribute information of the obstacle from the map.

9. The method of claim 8, wherein, The installation parameters include a candidate height and / or a candidate pitch angle of the image acquisition device, and before the determining the static objects in the initial collection range from the map as the obstacle, the method further comprises: Determining an obstacle screening height condition based on the candidate height and / or the candidate pitch angle of the image acquisition device; The determining the static objects in the initial collection range from the map as the obstacle comprises: Determining the static objects in the initial collection range that satisfy the obstacle screening height condition from the map as the obstacle.

10. The method according to any one of claims 1 to 5, characterized in that, The method further comprises: Visualizing and outputting the visual field of the image acquisition device and the obstacle.

11. A method of construction planning, characterized by, The method comprises: Obtaining attribute information of a prospective construction object in a region to be planned, and device parameters and installation parameters of an image acquisition device; the image acquisition device is used to acquire images of the region to be planned; Determining an obstacle and attribute information of the obstacle from the prospective construction object based on the device parameters and the installation parameters; the obstacle is the prospective construction object affecting a collection field of view of the image acquisition device; Obtaining coordinates of the obstacle in a polar coordinate system based on the attribute information of the obstacle; a pole point of the polar coordinate system is related to the installation parameters; Determining a visual field of the image acquisition device based on the coordinates of the obstacle in the polar coordinate system; the visual field is a region in the collection field of view of the image acquisition device that is not blocked by the obstacle; Determining a construction planning result of the region to be planned based on the visual field.

12. A method of monitoring a layout plan, characterized by, The method comprises: Obtain device parameters of an image acquisition device and planned installation parameters; the image acquisition device is used for image acquisition on a region where the image acquisition device is to be laid out; Determine, based on the device parameters and the planned installation parameters, an obstacle in the region and attribute information of the obstacle that affects a collection field of view of the image acquisition device from a map; Obtain, based on the attribute information of the obstacle, a coordinate of the obstacle in a polar coordinate system; wherein a pole point of the polar coordinate system is related to the installation parameters; Determine a visual field of the image acquisition device based on the coordinate of the obstacle in the polar coordinate system; When it is determined that the visual field meets a preset condition, determine that the planned installation parameters are target installation parameters of the image acquisition device.

13. An electronic device, comprising: Comprise: A processor and a memory; The processor is in communication connection with the memory; The memory stores computer instructions; The processor executes the computer instructions stored in the memory to realize the method in any one of claims 1-12.

14. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to realize the method in any one of claims 1-12.

15. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to realize the method in any one of claims 1-12.

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