Visualization method and device of scene entity and electronic equipment

Abstract

The invention relates to the technical field of intelligent mines and image processing, and discloses a scene entity visualization method and device and electronic equipment. The method comprises the following steps: acquiring information entity data; determining a visual area according to a preset observation range and the position coordinates of the observation viewpoint, wherein the observation viewpoint is the position of the analog image acquisition equipment; according to the visual area, performing position screening on the acquired information entity data to obtain a target information entity; and performing visual rendering on the target information entity to obtain visual target scene data. According to the invention, the visualization efficiency of the scene entity is improved.

Description

Technical Field

[0001] The present application relates to the fields of smart mines and image processing, and in particular to a method, device and electronic equipment for visualizing scene entities. Background Art

[0002] With the continuous improvement of intelligent and information construction in mines, real-time monitoring and display of the operating status of mining equipment has become increasingly important in the visualization application of mining scenes. Existing mining visualization technologies deploy sensors and cameras in mining areas to collect basic data such as the location coordinates and operating status of mining equipment, and use 3D modeling and scene rendering technology to achieve visualization of the entire mining scene. These technologies have been widely used in equipment management, job scheduling, and safety monitoring in open-pit mines.

[0003] However, in actual applications, due to the large number of mining equipment, the visualization system needs to process and render a large amount of real-time data at the same time. When visualizing the scene, the data of all devices will be loaded and rendered indiscriminately. This processing method not only wastes system resources, but also affects the operating performance of the visualization system, especially in equipment-intensive areas, where the system response speed will be significantly reduced. Summary of the invention

[0004] The present application provides a method, device and electronic device for visualizing a scene entity, which are used to improve the efficiency of visualizing the scene entity.

[0005] In a first aspect, the present application provides a method for visualizing a scene entity, the method comprising: acquiring information entity data; determining a visible area according to a preset observation range and the position coordinates of an observation viewpoint, wherein the observation viewpoint is the position of a simulated image acquisition device; performing position screening on the acquired information entity data according to the visible area to obtain a target information entity; and visually rendering the target information entity to obtain visualized target scene data.

[0006] In a second aspect, the present application provides a scene entity visualization device, the scene entity visualization device comprising:

[0007] An acquisition module, used to acquire information entity data;

[0008] An analysis module, used to determine the visible area according to a preset observation range and the position coordinates of an observation viewpoint, wherein the observation viewpoint is the position of a simulated image acquisition device;

[0009] A screening module, used to perform position screening on the acquired information entity data according to the visible area to obtain a target information entity;

[0010] The rendering module is used to perform visual rendering on the target information entity to obtain visualized target scene data.

[0011] The third aspect of the present application provides an electronic device, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via a bus, and when the machine-readable instructions are executed by the processor, the steps of the scene entity visualization method are executed.

[0012] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for visualizing scene entities.

[0013] In the technical solution provided by this application, a complete data acquisition system is established by acquiring information entity data, ensuring that the real-time status of all devices in the scene can be accurately recorded and transmitted. Secondly, the method of determining the visible area according to the preset observation range and the observation viewpoint position coordinates realizes the accurate demarcation of the observation area. By simulating the actual position of the image acquisition device, the determination of the visible area is more in line with the actual observation needs, and the accuracy of scene observation is improved; thirdly, the processing method of position screening of the acquired information entity data according to the determined visible area effectively reduces the amount of data to be processed, retains only the target information entities that really need to be displayed, avoids the invalid processing of entities outside the field of view, and greatly improves the operation efficiency of the system; finally, the technical means of visual rendering of the screened target information entities ensures the real-time and smoothness of the scene display, so that users can clearly observe the real-time status of the equipment in the area of ​​interest. Overall, when processing mining scenes with large-scale data volumes, this solution not only ensures the integrity and accuracy of the scene display, but also significantly improves the processing efficiency through the close cooperation of data acquisition, area determination, intelligent screening and visual rendering. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0015] Figure 1 A schematic diagram of an embodiment of a method for visualizing a scene entity in an embodiment of the present application;

[0016] Figure 2 A schematic diagram of an embodiment of a visualization device for scene entities in an embodiment of the present application;

[0017] Figure 3 Schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0018] Embodiments of the present application provide a method, device and electronic device for visualizing a scene entity. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or precedence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than the content illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0019] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of a method for visualizing a scene entity in an embodiment of the present application includes:

[0020] Step S101, obtaining information entity data;

[0021] Step S102, determining the visible area according to the preset observation range and the position coordinates of the observation viewpoint, where the observation viewpoint is the position of the simulated image acquisition device;

[0022] Step S103: performing position screening on the acquired information entity data according to the visible area to obtain the target information entity;

[0023] Step S104: Visually render the target information entity to obtain visualized target scene data.

[0024] In an optional embodiment, the information entity is an entity with specified motion characteristics, and the specified motion characteristics include: time randomness and / or position randomness.

[0025] It is understandable that the execution subject of the present application may be a visualization device of a scene entity, or may be a terminal or a server, which is not specifically limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0026] Specifically, firstly, information entity data is acquired, and the information entity includes but is not limited to basic attributes such as mining equipment identification, type, location coordinates, motion state, etc. These basic attribute data are collected specifically through sensors installed on the mining equipment, and the data collection frequency is, for example, once per second.

[0027] Optionally, when determining the visible area based on the preset observation range and the observation viewpoint position coordinates, the observation viewpoint actually represents the installation position of the simulated image acquisition device. A spatial reference is established through a three-dimensional coordinate system, the observation viewpoint is set as the coordinate origin (0, 0, 0), and then the cone parameters are set, including the horizontal viewing angle, the vertical viewing angle, and the observation distance, to construct a visible area in the shape of a cone. For example, the horizontal viewing angle is 120 degrees, the vertical viewing angle is 90 degrees, and the observation distance is 500 meters. These parameters are used to calculate the six planes of a conical visible area (near plane, far plane, left plane, right plane, upper plane, and lower plane).

[0028] Optionally, when performing position screening on the acquired information entity data, a frustum clipping algorithm can be used to determine whether the information entity is within the visible area. The algorithm makes a judgment by calculating the distance from the information entity position coordinates to the six clipping planes of the frustum. Set the plane equation ax+by+cz+d=0, where a, b, c, and d are preset equation coefficients. Substitute the information entity coordinates (x, y, z) into the equation. If the result is a positive value, it means that the point is on the front of the plane; if it is a negative value, it means that it is on the back of the plane. Judge the six clipping planes one by one, and only information entities that are all located on the front are retained as target information entities.

[0029] Optionally, the visualization rendering process of the target information entity includes steps such as space transformation, viewpoint projection, and scene combination. First, space transformation is performed to convert the world coordinates of the target information entity into observation coordinates; then viewpoint projection is performed to project the three-dimensional coordinates onto a two-dimensional screen; finally, scene combination is performed to combine the projected coordinates with entity attributes (such as color, material, etc.) to generate the final visualization scene.

[0030] Optionally, the specified motion characteristics of the information entity include time randomness and position randomness. Time randomness is reflected in the fact that the time interval of device motion is not fixed, while position randomness is reflected in the fact that the device motion trajectory is uncertain.

[0031] For example, there are 5 mining trucks running in the mining area, and each truck collects data once a second. At a certain moment, the simulated image acquisition device is located at the coordinates (0, 0, 50), with a horizontal viewing angle of 120 degrees, a vertical viewing angle of 90 degrees, and an observation distance of 500 meters. For a mining truck located at coordinates (100, 200, 0), its coordinates are substituted into the equations of six clipping planes: near plane 0.1x+0.2y+0.1z+10=31, far plane -0.1x-0.2y-0.1z+500=460, left plane 0.866x-0.5y+0=36.6, right plane -0.866x-0.5y+0=133.4, upper plane 0x+0.866y+0.5z=273.2, lower plane 0x-0.866y+0.5z=123.2, and the calculation results are all positive values, indicating that the mining truck is located inside the viewing cone, and it is retained as the target information entity. The mining truck has random characteristics, the speed fluctuates between 20-40km / h, and the running route changes dynamically according to the collection and unloading points, showing obvious time randomness and position randomness. After space transformation and viewpoint projection processing, the real-time operating status of the mining truck is finally clearly displayed on the screen.

[0032] In the embodiment of the present application, by acquiring information entity data, a complete data acquisition system is established to ensure that the real-time status of all devices in the scene can be accurately recorded and transmitted. Secondly, the method of determining the visible area according to the preset observation range and the observation viewpoint position coordinates realizes the accurate demarcation of the observation area. By simulating the actual position of the image acquisition device, the determination of the visible area is more in line with the actual observation needs, and the accuracy of scene observation is improved; thirdly, the processing method of position screening of the acquired information entity data according to the determined visible area effectively reduces the amount of data to be processed, and only retains the target information entities that really need to be displayed, avoiding the invalid processing of entities outside the field of view, and greatly improving the operation efficiency of the system; finally, the technical means of visual rendering of the screened target information entities ensures the real-time and smoothness of the scene display, so that the user can clearly observe the real-time status of the equipment in the area of ​​interest. Overall, when processing mining scenes with large-scale data volumes, this solution not only ensures the integrity and accuracy of the scene display, but also significantly improves the processing efficiency through the close cooperation of data acquisition, area determination, intelligent screening and visual rendering.

[0033] In an optional embodiment, the step of performing location screening on the acquired information entity data includes:

[0034] (1) performing position topological relationship detection on the coordinate data of each information entity in the acquired information entity data and the visible area to obtain a topological relationship;

[0035] (2) Determine the type of the topological relationship and determine the target information entity that has a containment relationship and / or an intersection relationship with the visible area.

[0036] Optionally, the coordinate data of each information entity is obtained, and the coordinate data includes the location information (x, y, z) of the entity in three-dimensional space. Position topological relationship detection is to determine the spatial relationship between the information entity and the visible area, involving three basic relationship types: inclusion, intersection and separation. Among them, the inclusion relationship indicates that the information entity is completely located inside the visible area, the intersection relationship indicates that the information entity is partially located inside the visible area, and the separation relationship indicates that the information entity is completely outside the visible area. The specific topological relationship detection adopts the ray method and the spatial analysis method. The ray method determines the topological relationship by emitting rays outward from the position of the information entity and calculating the number of intersections between the rays and the boundary of the visible area. The spatial analysis method determines the positional relationship by calculating the distance from the information entity to each boundary surface of the visible area. These two methods need to be calculated for each information entity to ensure the accuracy of the detection results.

[0037] Optionally, in the process of determining the type of topological relationship, the intersection data obtained by the ray method and the distance data obtained by the spatial analysis method are first obtained. When the number of intersections is 0 and all boundary surface distances are positive values, it is determined to be a containment relationship; when the number of intersections is not 0 and there are positive and negative distance values, it is determined to be an intersection relationship; when the number of intersections is 0 and all boundary surface distances are negative values, it is determined to be a separation relationship. Through this determination method, the specific topological relationship type between each information entity and the visible area is accurately identified. For information entities whose determination results are a containment relationship or an intersection relationship, they are marked as target information entities and retained for subsequent processing. Information entities whose determination results are a separation relationship are directly eliminated without subsequent processing, thereby achieving effective screening of information entities. This screening method based on topological relationships can accurately identify entity objects that need to be visualized.

[0038] For example, in a mining area, the observation viewpoint coordinates are set to (0, 0, 50), and the visible area is a cone with this point as the vertex, a horizontal viewing angle of 120 degrees, a vertical viewing angle of 90 degrees, and an observation distance of 500 meters. When performing topological relationship detection on an excavator located at the coordinates (100, 200, 20), firstly, a ray is emitted from this point to obtain the intersection data with the six faces of the cone; at the same time, the distance from this point to the six faces is calculated: the near plane distance is 31 meters, the far plane distance is 460 meters, the left plane distance is 36.6 meters, the right plane distance is 133.4 meters, the upper plane distance is 273.2 meters, and the lower plane distance is 123.2 meters. Since the number of intersections is 0 and all distances are positive, it is determined that the excavator and the visible area are in a containment relationship and it is retained as the target information entity. Another mining truck located at the coordinates (450, 100, 30) has two intersection points obtained through ray detection, and the calculated boundary surface distances have positive and negative values ​​(near plane -20 meters, far plane 380 meters, left plane 25 meters, right plane -15 meters, upper plane 200 meters, lower plane 150 meters), which is determined to be in an intersection relationship with the visible area and is also retained as a target information entity. For the loader located at the coordinates (-300, 600, 40), all boundary surface distances are negative values, which is determined to be a separation relationship and is removed.

[0039] In an optional embodiment, the rendering process is stopped for the information entity whose topological relationship with the visible area changes from an intersection relationship to a separation relationship.

[0040] In an optional embodiment, visual rendering is performed on the target information entity to obtain real-time scene data, including:

[0041] (1) Performing spatial transformation calculation on the position coordinates of the target information entity to obtain display coordinate data;

[0042] (2) extracting attributes from the state information of the target information entity to obtain display attribute data;

[0043] (3) performing viewpoint projection processing on the display coordinate data to obtain screen projection data, and performing graphic parameter mapping on the display attribute data to obtain drawing parameter data;

[0044] (4) Perform scene combination on the screen projection data and the drawing parameter data to obtain scene display data, and perform graphic drawing on the scene display data to obtain real-time scene data.

[0045] Specifically, by calculating the topological relationship between the information entity and the visible area in real time, when it is detected that an information entity changes from an intersecting state to a separated state, the rendering of the entity is immediately stopped to save computing resources. The change of the topological relationship is determined by comparing the results of two consecutive detections. If the first detection is an intersecting relationship (that is, some coordinate points are in the visible area), and the second detection becomes a separated relationship (that is, all coordinate points are outside the visible area), it is determined that a relationship change has occurred.

[0046] For the target information entity that needs to be rendered, the space transformation calculation is first performed to convert the world coordinates of the entity into the observation coordinates. This process includes two steps: translation transformation and rotation transformation. The translation transformation moves the coordinate origin from the world coordinate system to the observation coordinate system, and the rotation transformation adjusts the coordinate axis direction to match the observation angle. The display coordinate data obtained after the transformation reflects the exact position of the entity in the observation space. At the same time, the attribute extraction of the state information of the target information entity is performed, including information such as equipment type, operating status, speed, and load. These original attribute data are standardized to obtain display attribute data. The standardization process uniformly converts attribute values ​​of different dimensions into a specific range to facilitate subsequent parameter mapping. Next, the display coordinate data is subjected to viewpoint projection processing to project the coordinates in the three-dimensional space onto the two-dimensional screen plane. The projection process adopts perspective projection, calculates the projection matrix according to the viewpoint position, and maps the space coordinates to screen coordinates. At the same time, the display attribute data is subjected to graphic parameter mapping to convert the attribute values ​​into visual parameters such as color, size, and transparency. Finally, the screen projection data and drawing parameter data are combined into a scene, and the position and visual effect information of all graphic elements are integrated to form complete scene display data, and then the final real-time scene data is obtained through graphic drawing.

[0047] For example, the initial position coordinates of a mining truck are (200, 300, 20), which intersects with the visible area. As the truck moves to (520, 450, 20), the topological relationship detection finds that the distances to all boundary surfaces of the visible area are negative, and it is determined to be a separation relationship, and the rendering of the truck is immediately stopped. For another working excavator located at (150, 250, 10), firstly, its world coordinates are converted into observation coordinates (-150, -250, -40) with the observation point (0, 0, 50) as the origin through spatial transformation. At the same time, its status information is extracted: equipment number EX001, operating status "normal", operating speed 15km / h, bucket load 80%. These attributes are mapped to display parameters after standardization: normal state is represented by green, operating speed is represented by line thickness, and load rate is represented by filling degree.

[0048] Then, through perspective projection matrix calculation, the observation coordinates (-150, -250, -40) are projected onto the screen coordinates (800, 600), and combined with the mapped drawing parameters (color is RGB (0, 255, 0), line width is 2 pixels, and fill rate is 0.8), the real-time working status of the excavator is finally clearly displayed on the screen. The whole process realizes the precise conversion from three-dimensional space data to two-dimensional display images, providing intuitive visualization effects for real-time monitoring of mining equipment.

[0049] In an optional embodiment, determining the visible area according to a preset viewing angle range and the position coordinates of the observation viewpoint includes:

[0050] (1) determining a target viewing angle range based on an image acquisition viewing angle of a simulated image acquisition device and a preset viewing angle range;

[0051] (2) Decomposing the target viewing angle range to obtain horizontal viewing angle and vertical viewing angle;

[0052] (3) Calculate the rays for the horizontal and vertical viewing angles respectively to obtain the sight direction, and construct the view cone for the position coordinates and the view direction to obtain the spatial view cone data;

[0053] (4) Extracting the boundaries of the spatial viewing cone data to obtain visible range boundary data, and determining the region of the visible range boundary data to obtain the visible region.

[0054] Optionally, in the process of visualizing the mine scene, the preset observation range is first calculated based on the inherent parameters of the analog image acquisition device and the preset viewing angle range. The analog image acquisition device usually has its inherent image acquisition viewing angle, such as a 120-degree horizontal field of view and a 90-degree vertical field of view, while the preset viewing angle range is the expected observation range set according to the actual monitoring needs, such as a 150-degree horizontal field of view and a 100-degree vertical field of view. By taking the intersection of the two, the final target viewing angle range is obtained to ensure that it does not exceed the physical limitations of the equipment and meets the actual observation needs. After the target viewing angle range is determined, angle decomposition processing is required to decompose the overall viewing angle range into two independent components: horizontal viewing angle and vertical viewing angle. Angle decomposition uses a triangular decomposition method to project the spatial angle on the horizontal plane and the vertical plane respectively. This decomposition makes subsequent ray calculations more convenient and also facilitates the construction of the viewing cone.

[0055] Optionally, ray calculations are performed on the decomposed horizontal and vertical viewing angles to determine the sight direction. Ray calculation is based on the angle bisector principle. First, the angle bisector of the viewing angle is determined as the main sight direction, and then the boundary rays are determined on both sides of the main sight direction according to the size of the viewing angle. Combining the position coordinates of the simulated image acquisition device and the calculated sight direction, a quadrangular pyramid is used to approximate the spatial view cone. The view cone is surrounded by six planes, including a near plane, a far plane, a left plane, a right plane, an upper plane, and a lower plane. After the spatial view cone is constructed, the boundary data of the visible range is obtained by a boundary extraction algorithm. The boundary extraction process is obtained by calculating the intersection lines of each face of the view cone, and these intersection lines constitute the spatial boundary of the visible area. Finally, the spatial range of the entire visible area is determined based on the boundary data.

[0056] For example, the simulated image acquisition device installed at a commanding height is located at the coordinates (0, 0, 50). The parameters of the device itself are 120 degrees horizontal field of view and 90 degrees vertical field of view. The preset expected observation range is 150 degrees horizontal field of view and 100 degrees vertical field of view. After parameter comparison, the target viewing angle range is finally determined to be 120 degrees horizontally (the smaller value) and 90 degrees vertically (the smaller value). After decomposing this target viewing angle range, the viewing angle on the horizontal plane is plus or minus 60 degrees (a total of 120 degrees), and the viewing angle on the vertical plane is 45 degrees up and 45 degrees down (a total of 90 degrees). Based on these angle values, the ray direction is calculated: the main line of sight direction is (0, 1, 0), the horizontal boundary rays are (-0.866, 0.5, 0) and (0.866, 0.5, 0), and the vertical boundary rays are (0, 0.707, 0.707) and (0, 0.707, -0.707).

[0057] Combining the device position coordinates (0, 0, 50) and these ray directions, a spatial viewing cone is constructed. The near plane distance is set to 10 meters and the far plane distance is set to 500 meters, and the six plane equations of the viewing cone are obtained. By calculating the intersection of these planes, 12 spatial boundary lines are obtained, and the space surrounded by these boundary lines is the final visible area. In this area, the excavator at the coordinates (100, 200, 20) is completely visible, while the mining truck at the coordinates (-300, 400, 30) is partially visible, and the loader at the coordinates (600, 100, 10) is completely invisible.

[0058] In an optional embodiment, determining the visible area according to the preset area range and the position coordinates of the observation viewpoint includes:

[0059] (1) Determine the image acquisition area according to the image acquisition viewing angle and position coordinates of the simulated image acquisition device;

[0060] (2) Determine the visible area based on the image acquisition area and the preset area range.

[0061] Specifically, the acquisition area is calculated based on the actual parameters of the simulated image acquisition device. The main parameters of the simulated image acquisition device include the horizontal field of view angle, the vertical field of view angle, and the acquisition distance. The position coordinates of the device define the starting point of the acquisition area, and a complete image acquisition area can be calculated by combining these parameters. The image acquisition area is calculated using the fan projection method, with the device position as the vertex, and a fan-shaped acquisition space is constructed based on the field of view angle and the acquisition distance. The horizontal field of view angle of the acquisition device determines the expansion angle of the sector, the vertical field of view angle determines the height range of the acquisition space, and the acquisition distance defines the radius of the sector. The three-dimensional acquisition space constructed in this way accurately reflects the actual acquisition capability range of the device.

[0062] The preset area range is a specific area delineated according to actual monitoring needs, usually expressed as a polygonal area connected by multiple coordinate points. This area represents the actual spatial range that needs to be monitored. The final visible area is obtained by calculating the intersection of the image acquisition area and the preset area range, specifically using the spatial intersection operation method. The intersection operation first determines the boundary lines of the two areas, then calculates the intersection points of these boundary lines, and finally the space surrounded by these intersection points is the final visible area.

[0063] For example: the simulated image acquisition device is installed at a height of 50 meters, with coordinates (0, 0, 50), and the device parameters are 120 degrees horizontal field of view, 90 degrees vertical field of view, and 500 meters effective acquisition distance. The image acquisition area calculated by the fan projection method is: with (0, 0, 50) as the vertex, it expands 120 degrees on the horizontal plane (i.e. from -60 degrees to +60 degrees), covers 45 degrees up and down in the vertical direction (i.e. from the ground plane to 90 meters), and has a radius of 500 meters. The preset area range is a rectangular area defined by four coordinate points: A (-200, 0, 0), B (200, 0, 0), C (200, 400, 0), and D (-200, 400, 0). This area covers the main mining operation area. Perform spatial intersection operation on the image acquisition area and the preset area, and first calculate the intersection line of the fan-shaped area and the rectangular area: the coordinates of the intersection at 100 meters away from the device are (-86.6, 50, 0) and (86.6, 50, 0), the intersection at 200 meters are (-173.2, 100, 0) and (173.2, 100, 0), and the intersection at 300 meters are (-200, 150, 0) and (200, 150, 0).

[0064] The final visible area is determined by these intersection points: an irregular polygon space with (0, 0, 50) as the vertex and a curved bottom. In this visible area, all mining equipment can be effectively monitored. For example, the excavator at the coordinates (100, 200, 20) is completely within the visible area, and its working status can be clearly captured; while the loader at the coordinates (-180, 380, 15) is within the preset area, but because it exceeds the effective field of view of the acquisition device, it is not within the final visible area. This method of determining the visible area based on the area range can effectively combine equipment capabilities and actual needs to achieve accurate scene monitoring.

[0065] The above describes the method for visualizing the scene entity in the embodiment of the present application. The following describes the device for visualizing the scene entity in the embodiment of the present application. Figure 2 In one embodiment of the present application, a visualization device for scene entities includes:

[0066] Acquisition module 201, used to acquire information entity data;

[0067] An analysis module 202 is used to determine the visible area according to a preset observation range and the position coordinates of an observation viewpoint, where the observation viewpoint is the position of a simulated image acquisition device;

[0068] A screening module 203 is used to perform position screening on the acquired information entity data according to the visible area to obtain a target information entity;

[0069] The rendering module 204 is used to perform visual rendering on the target information entity to obtain visualized target scene data.

[0070] The screening module 203 is specifically used to: perform position topological relationship detection on the coordinate data of each information entity in the acquired information entity data and the visible area to obtain a topological relationship; perform type determination on the topological relationship to determine a target information entity that has a containment relationship and / or an intersection relationship with the visible area.

[0071] The visualization device of the scene entity further comprises:

[0072] The conversion module is used to stop rendering the information entity whose topological relationship with the visible area is changed from an intersection relationship to a separation relationship.

[0073] The screening module 204 is specifically used to: perform spatial transformation calculation on the position coordinates of the target information entity to obtain display coordinate data; perform attribute extraction on the state information of the target information entity to obtain display attribute data; perform viewpoint projection processing on the display coordinate data to obtain screen projection data, and perform graphic parameter mapping on the display attribute data to obtain drawing parameter data; perform scene combination on the screen projection data and the drawing parameter data to obtain scene display data, and perform graphic drawing on the scene display data to obtain real-time scene data.

[0074] The analysis module 202 is specifically used to: determine the target viewing angle range based on the image acquisition viewing angle of the simulated image acquisition device and the preset viewing angle range; perform angle decomposition on the target viewing angle range to obtain a horizontal viewing angle and a vertical viewing angle; perform ray calculations on the horizontal viewing angle and the vertical viewing angle respectively to obtain a line of sight direction, and perform a cone construction on the position coordinates and the line of sight direction to obtain spatial cone data; perform boundary extraction on the spatial cone data to obtain visible range boundary data, and perform area determination on the visible range boundary data to obtain a visible area.

[0075] The analysis module 202 may also be specifically used to: determine an image acquisition area according to an image acquisition viewing angle and position coordinates of a simulated image acquisition device; and determine a visible area based on the image acquisition area and the preset area range.

[0076] Through the cooperation of the above components, a complete data collection system is established by acquiring information entity data, ensuring that the real-time status of all equipment in the scene can be accurately recorded and transmitted. Secondly, the method of determining the visible area according to the preset observation range and the observation viewpoint position coordinates realizes the accurate demarcation of the observation area. By simulating the actual position of the image acquisition device, the determination of the visible area is more in line with the actual observation needs, and the accuracy of scene observation is improved; thirdly, the processing method of position screening of the acquired information entity data according to the determined visible area effectively reduces the amount of data to be processed, retains only the target information entities that really need to be displayed, avoids the invalid processing of entities outside the field of view, and greatly improves the operation efficiency of the system; finally, the technical means of visual rendering of the screened target information entities ensures the real-time and smoothness of the scene display, so that users can clearly observe the real-time status of the equipment in the area of ​​concern. Overall, when processing mining scenes with large-scale data volumes, this solution not only ensures the integrity and accuracy of the scene display, but also significantly improves the processing efficiency through the close cooperation of data acquisition, area determination, intelligent screening and visual rendering.

[0077] Based on the same technical concept, the embodiment of the present application also provides an electronic device. Figure 3 As shown, it is a schematic diagram of the structure of the electronic device 300 provided in the embodiment of the present application, including a processor 301, a memory 302, and a bus 303. Among them, the memory 302 is used to store execution instructions, including a memory 3021 and an external memory 3022; the memory 3021 here is also called an internal memory, which is used to temporarily store the operation data in the processor 301, and the data exchanged with the external memory 3022 such as a hard disk. The processor 301 exchanges data with the external memory 3022 through the memory 3021. When the electronic device 300 is running, the processor 301 communicates with the memory 302 through the bus 303.

[0078] The present application also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein instructions are stored in the computer, and when the instructions are executed on a computer, the computer executes the steps of the method for visualizing the scene entity.

[0079] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0080] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0081] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for visualizing a scene entity, characterized in that: The following steps are involved: Get information entity data; Determine the visible area according to the preset observation range and the position coordinates of the observation viewpoint, wherein the observation viewpoint is the position of the simulated image acquisition device; According to the visible area, position screening is performed on the acquired information entity data to obtain a target information entity; The target information entity is visually rendered to obtain visualized target scene data.

2. The method according to claim 1, characterized in that The information entity is an entity with specified motion characteristics, and the specified motion characteristics include: time randomness and / or position randomness.

3. The method according to claim 1, characterized in that According to the visible area, position screening is performed on the acquired information entity data to obtain a target information entity, including: Performing position topological relationship detection on the coordinate data of each information entity in the acquired information entity data and the visible area to obtain a topological relationship; The type of the topological relationship is determined to determine the target information entity having a containment relationship and / or an intersection relationship with the visible area.

4. The method according to claim 3, characterized in that Also includes; For the information entity whose topological relationship with the visible area changes from an intersection relationship to a separation relationship, the rendering process is stopped.

5. The method according to claim 1, characterized in that: Visually render the target information entity to obtain real-time scene data, including: Performing spatial transformation calculation on the position coordinates of the target information entity to obtain display coordinate data; Extracting attributes from the state information of the target information entity to obtain display attribute data; Performing viewpoint projection processing on the display coordinate data to obtain screen projection data, and performing graphic parameter mapping on the display attribute data to obtain drawing parameter data; The screen projection data and the drawing parameter data are scene-combined to obtain scene display data, and graphics are drawn on the scene display data to obtain real-time scene data.

6. The method according to claim 1, characterized in that The preset observation range is a preset viewing angle range, and the visible area is determined according to the preset viewing angle range and the position coordinates of the observation viewpoint, including: Determining a target viewing angle range based on the image acquisition viewing angle of the simulated image acquisition device and the preset viewing angle range; Decomposing the target viewing angle range by angle to obtain a horizontal viewing angle and a vertical viewing angle; Performing ray calculations on the horizontal viewing angle and the vertical viewing angle respectively to obtain a sight line direction, and constructing a view cone on the position coordinates and the view line direction to obtain spatial view cone data; Boundary extraction is performed on the spatial viewing cone data to obtain visible range boundary data, and area determination is performed on the visible range boundary data to obtain a visible area.

7. The method according to claim 1, characterized in that The preset observation range is a preset area range, and the visible area is determined according to the preset area range and the position coordinates of the observation viewpoint, including: Determine the image acquisition area according to the image acquisition viewing angle and position coordinates of the simulated image acquisition device; A visible area is determined based on the image acquisition area and the preset area range.

8. A visualization device for scene entities, characterized in that: The visualization device of the scene entity comprises: An acquisition module, used to acquire information entity data; An analysis module, used to determine the visible area according to a preset observation range and the position coordinates of an observation viewpoint, wherein the observation viewpoint is the position of a simulated image acquisition device; A screening module, used to perform position screening on the acquired information entity data according to the visible area to obtain a target information entity; The rendering module is used to perform visual rendering on the target information entity to obtain visualized target scene data.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for visualizing scene entities as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, a method for visualizing a scene entity as described in any one of claims 1 to 7 is implemented.

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