Panoramic view resource service engine-based rendering method and device, equipment and medium

Abstract

This invention relates to the field of data processing technology, providing a rendering method, apparatus, device, and medium based on a panoramic resource service engine. It can reconstruct the spatial coordinate system of a UAV panoramic dome image based on surveying vector data, solving the visual displacement problem between the virtual redline and real-world features during 360° rotation. It performs attitude compensation rendering on the reconstructed dome image based on real-time viewpoint data and a nonlinear mapping model, ensuring the redline always conforms to the real-world terrain without floating. It uses pixel-by-pixel depth mapping to perform occlusion culling on the dynamic redline layer, and then composites the occluded dynamic redline layer with the reconstructed dome image, enabling the redline to be deeply embedded in the real-world scene, significantly enhancing visual realism. Finally, it performs interactive rendering of the target sub-region based on resource flow information and a nonlinear mapping model, thereby achieving an interactive panoramic display of resource flow information.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a rendering method, apparatus, device and medium based on a panoramic view resource service engine. Background Technology

[0002] With the deepening of market-based transactions of natural resources, traditional two-dimensional map displays are no longer sufficient to meet users' needs for intuitive understanding of land location, real-world environment, and transaction status. Therefore, how to provide a panoramic view of the resource transfer status of a designated area has become an urgent problem to be solved.

[0003] The currently used panoramic display solutions still have the following shortcomings in practical applications: (1) Insufficient spatial alignment accuracy.

[0004] Drone panoramic dome images suffer from spherical aberration, edge distortion, and lens nonlinear distortion. Since the land parcel boundary line is a high-precision survey coordinate, existing linear coordinate transformation methods cannot effectively compensate for the nonlinear errors of panoramic projection. This causes significant visual displacement between the virtual boundary line and the real-world features when rotating 360°. The boundary line is prone to drift at the edge of the viewpoint, which seriously affects the accuracy of users' spatial judgment of the land parcel boundary.

[0005] (2) Lack of visual realism.

[0006] In real-world scenarios, obstructions such as trees and temporary buildings can cover the land boundary line, causing the boundary line to appear to float above the obstructions. This makes it impossible to present a true spatial occlusion relationship and reduces the accuracy of users' judgment of the land's spatial location.

[0007] (3) Resource transfer information is not synchronized.

[0008] Current panoramic dashboards typically only display geographical location information, and users cannot view the real-time flow of resources. Summary of the Invention

[0009] In view of the above, it is necessary to provide a rendering method, device, equipment and medium based on a panoramic resource service engine, which aims to solve the problems of insufficient spatial alignment accuracy, lack of visual realism and asynchronous resource flow information during resource rendering.

[0010] A rendering method based on a panoramic view resource service engine, the rendering method based on the panoramic view resource service engine includes: Collect mapping vector data and UAV panoramic dome images of the target area; Based on the mapping vector data, the spatial coordinate system of the UAV panoramic dome image is reconstructed to obtain the reconstructed dome image and nonlinear mapping model, and the reconstructed dome image is rendered to the target platform connected to the panoramic viewing resource service engine. The client collects real-time view data of users on the target platform, and performs attitude compensation rendering on the reconstructed dome image based on the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view. Generate a pixel-by-pixel depth map of the reconstructed dome image; The dynamic red line layer is occluded and culled using the pixel-by-pixel depth mapping, and the occluded and culled dynamic red line layer is then combined with the reconstructed dome image to obtain a panoramic red line image. When a resource transfer event query command triggered based on a target sub-region in the target region is detected, resource transfer information is obtained; Based on the resource flow information and the nonlinear mapping model, the target sub-region is interactively rendered to obtain an interactive panoramic view of resource flow.

[0011] A rendering apparatus based on a panoramic view resource service engine, the rendering apparatus based on the panoramic view resource service engine comprising: The acquisition unit is used to acquire mapping vector data and UAV panoramic dome images of the target area. The reconstruction unit is used to reconstruct the spatial coordinate system of the UAV panoramic dome image based on the mapping vector data, obtain the reconstructed dome image and nonlinear mapping model, and render the reconstructed dome image to the target platform connected to the panoramic viewing resource service engine. The rendering unit is used to collect real-time view data of users on the target platform through the client, and perform attitude compensation rendering on the reconstructed dome image according to the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view. A generation unit is used to generate a pixel-by-pixel depth map of the reconstructed dome image; The compositing unit is used to perform occlusion removal processing on the dynamic red line layer using the pixel-by-pixel depth mapping, and to perform layer compositing of the dynamic red line layer after occlusion removal processing with the reconstructed dome image to obtain a red line panoramic image. The acquisition unit is used to acquire resource flow information when it receives a resource flow event triggered based on a target sub-region in the target region; The rendering unit is also used to interactively render the target sub-region based on the resource flow information and the nonlinear mapping model to obtain an interactive panoramic view of resource flow.

[0012] A computer device, the computer device comprising: A memory for storing at least one instruction; and a processor for executing the instructions stored in the memory to implement the rendering method based on the panoramic view resource service engine.

[0013] A computer-readable storage medium storing at least one instruction, which is executed by a processor in a computer device to implement the rendering method based on a panoramic view resource service engine.

[0014] As can be seen from the above technical solutions, this invention can reconstruct the spatial coordinate system of the UAV panoramic dome image based on the surveying vector data, solving the problem of visual displacement between the virtual red line and the real-world features during 360° rotation; it performs attitude compensation rendering on the reconstructed dome image based on real-time perspective data and a nonlinear mapping model, ensuring that the red line always conforms to the real-world terrain without floating; it uses pixel-by-pixel depth mapping to perform occlusion removal processing on the dynamic red line layer, and then combines the occlusion-removed dynamic red line layer with the reconstructed dome image, enabling the red line to be deeply embedded in the real-world scene, significantly enhancing the visual realism; and it performs interactive rendering of the target sub-region based on resource flow information and a nonlinear mapping model, thereby achieving an interactive panoramic display of resource flow information. Attached Figure Description

[0015] Figure 1 This is a flowchart of a preferred embodiment of the rendering method based on the panoramic view resource service engine of the present invention.

[0016] Figure 2 This is a functional block diagram of a preferred embodiment of the rendering device based on the panoramic view resource service engine of the present invention.

[0017] Figure 3 This is a schematic diagram of the structure of a computer device that implements a preferred embodiment of the rendering method based on a panoramic view resource service engine according to the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] like Figure 1 The diagram shown is a flowchart of a preferred embodiment of the rendering method based on a panoramic resource service engine according to the present invention. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0020] The rendering method based on the panoramic view resource service engine is applied to one or more computer devices. The computer device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0021] The computer device can be any electronic product that can interact with the user, such as a personal computer, tablet computer, smartphone, personal digital assistant (PDA), game console, interactive network television (IPTV), smart wearable device, etc.

[0022] The computer equipment may also include network equipment and / or user equipment. The network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of hosts or network servers.

[0023] The server can be a standalone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0024] Artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0025] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0026] The network in which the computer device is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, and virtual private network (VPN).

[0027] S10 collects mapping vector data and UAV panoramic dome images of the target area.

[0028] In this embodiment, the target area can be an area with resource transfer needs, such as a residential community for sale, a city, or a village.

[0029] In this embodiment, the application programming interface of an authoritative organization can be called to obtain the land parcel boundary polygon (including metadata such as boundary point coordinates, ownership, and transaction status) of the target area in the WGS84 (World Geodetic System 1984) coordinate system, and use it as the mapping vector data.

[0030] The land parcel red line refers to the closed polygonal boundary line of the land parcel ownership boundary. The land parcel red line accurately delineates the spatial scope, ownership, and land use control boundaries of the land, and serves as the basis for natural resource transactions, planning approvals, and ownership registration.

[0031] The land parcel boundary line is a sequence of high-precision geographic coordinate points, which, when connected, form a closed polygon representing the physical boundary of the land parcel.

[0032] In a visualization scenario, the land parcel red line is represented as an outline superimposed on a map or panoramic image, used to intuitively identify the extent of the land parcel.

[0033] In this embodiment, the drone panoramic dome image refers to the dome image of the target area collected by the drone.

[0034] In this embodiment, in order to ensure the geometric integrity and image quality of the input data and provide a reliable basis for subsequent spatial alignment, the mapping vector data of the target area and the UAV panoramic dome image can also be preprocessed.

[0035] Specifically, topological checks can be performed on the mapping vector data, and geometric errors such as self-intersection and overlap can be corrected based on the check results; defogging and white balance correction can be performed on the UAV panoramic dome image to improve data quality.

[0036] S11, Based on the surveying vector data, the spatial coordinate system of the UAV panoramic dome image is reconstructed to obtain the reconstructed dome image and nonlinear mapping model, and the reconstructed dome image is rendered to the target platform connected to the panoramic viewing resource service engine.

[0037] In this embodiment, the step of reconstructing the spatial coordinate system of the UAV panoramic dome image based on the mapping vector data to obtain the reconstructed dome image and nonlinear mapping model includes: Identify ground feature points in the panoramic dome image of the UAV and extract the pixel coordinates of each ground feature point; Obtain the corresponding feature points for each ground feature point from the mapping vector data, and extract the geographic coordinates of each corresponding feature point; Construct control point pairs based on the pixel coordinates of each ground feature point and the geographic coordinates of each feature point with the same name; Initialize the parameters of the panoramic projection spherical model, and use the reprojection error of the control point pair as the objective function to iteratively solve the parameters of the panoramic projection spherical model using the Levenberg-Marquardt (LM) method. Construct the nonlinear mapping model based on the optimal parameters obtained from the solution; The spatial coordinate system of the UAV panoramic dome image is reconstructed using the nonlinear mapping model to obtain the reconstructed dome image.

[0038] Among them, SIFT (Scale-Invariant Feature Transform) or ORB (Oriented FAST and Rotated BRIEF) algorithms can be used to automatically identify ground feature points in the UAV panoramic dome image, such as road intersections and building corners.

[0039] The parameters of the panoramic projection spherical model may include, but are not limited to, sphere center offset, focal length, distortion coefficient, etc.

[0040] Through the above embodiments, spherical aberration and edge distortion of the panoramic dome image of the UAV can be eliminated, and a precise nonlinear mapping between pixel coordinates and geographic coordinates can be established, solving the problem of visual displacement between the virtual red line and real-world objects when rotating 360°.

[0041] In this embodiment, the target platform is a platform that can interact with users.

[0042] Specifically, the target platform provides interactive VR (Virtual Reality) scenes, allowing users to view different resource information through real-time operations (such as dragging the viewpoint or clicking on hotspots).

[0043] For example, the target platform can display a specific plot of land and its surrounding panoramic view, such as traffic conditions, supporting facilities, and current land status, by sliding left, right, up, and down.

[0044] The target platform can also provide some icons. When a specified icon is clicked, different observation points can be directly switched (such as viewing from the north side of the plot or from a bird's-eye view).

[0045] By clicking on the various function buttons on the target platform, users can also jump to different interfaces, such as the transaction interface and the map interface.

[0046] S12, real-time view data of users on the target platform is collected through the client, and the reconstructed dome image is rendered with attitude compensation based on the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view.

[0047] In this embodiment, the user can interact with the target platform through a client.

[0048] In this embodiment, the real-time view data may include pitch angle, yaw angle, roll angle, and field of view (FOV).

[0049] In this embodiment, the step of performing attitude compensation rendering on the reconstructed dome image based on the real-time viewpoint data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the viewpoint includes: Identify the redline polygons of each sub-region in the mapping vector data, and obtain the geographic coordinates of each vertex of each redline polygon; The geographic coordinates of each vertex are mapped to spherical coordinates using the nonlinear mapping model, and the spherical coordinates obtained after mapping are inversely calculated based on the real-time view data to obtain the dynamic redline layer.

[0050] For example, when a user looks up (Pitch=60°), the red line can automatically retract upwards and maintain its alignment with the outline of the real-world building.

[0051] Through the above embodiments, the perspective distortion of the red line layer can be corrected in real time according to the user's perspective, so that the red line always fits the real terrain without floating and achieves a smooth display that slides with the viewpoint.

[0052] S13, Generate a pixel-by-pixel depth map of the reconstructed dome image.

[0053] In this embodiment, the pixel-by-pixel depth map of the reconstructed dome image can be generated using the MiDaS (Multiple Depth Estimation Architectures Single Image Depth Prediction) model or a binocular stereo vision algorithm.

[0054] Among them, using the MiDaS model or binocular stereo vision algorithm requires no additional hardware or multi-view camera configuration, resulting in lower deployment costs.

[0055] S14, the dynamic red line layer is occluded and culled using the pixel-by-pixel depth mapping, and the dynamic red line layer after occlusion and culling is combined with the reconstructed dome image to obtain a red line panoramic image.

[0056] In this embodiment, the occlusion removal process of the dynamic red line layer using the pixel-by-pixel depth mapping includes: Traverse each red line pixel in the dynamic red line layer and query the depth corresponding to each red line pixel in the pixel-by-pixel depth map to obtain the depth of each red line. Semantic segmentation is performed on the reconstructed dome image to obtain the occlusion mask; Obtain each occlusion pixel in the occlusion mask, and query the depth corresponding to each occlusion pixel in the pixel-by-pixel depth map to obtain the depth of each occlusion. When a first red line depth is detected that is greater than the corresponding first occlusion depth, and the absolute difference between the first red line depth and the first occlusion depth is greater than or equal to a preset threshold, the red line pixel corresponding to the first red line depth is removed from the dynamic red line layer.

[0057] Specifically, a pre-trained DeepLabv3+ (Deep Convolutional Network atrousSpatial Pyramid Pooling) model can be used to perform semantic segmentation on the reconstructed dome image, obtaining mask images of occlusions such as vegetation, buildings, and temporary structures as the occlusion masks.

[0058] Specifically, after removing the red line pixel corresponding to the depth of the first red line from the dynamic red line layer, the pixel will not be rendered in subsequent rendering.

[0059] The preset threshold can be the optimal value obtained after analyzing historical data.

[0060] For example, when a tree obscures the red line, the pixels of the obscured part of the red line are automatically removed, and only the unobscured part is displayed, thus solving the problem of the red line floating on the tree.

[0061] In this embodiment, the step of combining the dynamic redline layer after occlusion removal processing with the reconstructed dome image to obtain the redline panoramic image includes: The dynamic redline layer after occlusion removal is superimposed on the reconstructed dome image layer by layer according to the hierarchical relationship on the Z-axis to obtain the redline panoramic image. Specifically, when a second red line depth is detected to be greater than the corresponding second occlusion depth and the absolute difference between the second red line depth and the second occlusion depth is less than the preset threshold, and / or the sub-region corresponding to the second red line depth is a high-priority region, the transparency is configured according to the absolute difference; and the red line pixels corresponding to the second red line depth are rendered semi-transparently to the reconstructed dome image according to the transparency. The transparency decreases as the absolute difference increases. Specifically, the smaller the absolute difference, the higher the transparency; the larger the absolute difference, the lower the transparency, to ensure a natural visual effect and conform to spatial logic.

[0062] Specifically, when a second red line depth is detected that is greater than the corresponding second occluder depth and the absolute difference between the second red line depth and the second occluder depth is less than the preset threshold, it can be determined as a depth overlap region. In this case, semi-transparent rendering is performed instead of direct cropping.

[0063] The high-priority area corresponds to high-value plots of land. Even if the red line is temporarily obstructed (such as trees or temporary fences), the visual continuity of the red line must be maintained to prevent users from misjudging the plot boundaries due to breaks in the red line. For example, the high-priority area can be plots under bidding or plots with high search volume.

[0064] Of course, the semi-transparent rendering of the corresponding plot red line can also be forced based on the user's choice (such as clicking the red line or plot label). In this case, the red line will be faintly visible under the occlusion, regardless of the depth of the occlusion, so that the user can check the complete boundary.

[0065] The above embodiments can effectively identify real-world obstructions, achieve deep embedding of the red line and the obstruction, and enhance visual realism.

[0066] In this embodiment, after obtaining the panoramic image of the red line, the method further includes: The flow heat data of each sub-region in the target region is detected, and a resource heat matrix is ​​constructed based on the flow heat data; Calculate the vector boundary complexity for each sub-region; The rendering weight of each sub-region is calculated based on the resource heat matrix, the real-time view data, and the vector boundary complexity. Based on the rendering weights, asynchronous loading of Level of Detail (LOD) is performed on each sub-region in the redline panorama.

[0067] For example, a long-lived connection (WebSocket) can be used to subscribe to the backend event stream and listen to indicators such as the bidding frequency (number of times the price of the land parcel changes per unit time), the number of users paying attention, and the remaining transaction time (the time from the current time to the transaction deadline) of each land parcel to be traded (i.e., sub-region) as the circulation popularity data.

[0068] The number of user followers can be a weighted sum of page views, unique visitors, favorites, and inquiries.

[0069] Furthermore, the bidding frequency and the number of users following can be normalized using Min-Max to map them to the [0,1] interval. The remaining transaction duration can be reverse normalized (the shorter the time, the higher the popularity), such as: 1 - (remaining transaction duration / total transaction duration).

[0070] The overall popularity score is calculated as follows: m * normalized bid frequency + n * normalized user follower count + p * inverse normalized remaining transaction time. Here, m, n, and p are weighting coefficients that can be configured based on experimental results.

[0071] Furthermore, the resource heat matrix can be constructed based on the comprehensive heat score, with each plot's unique identifier as the row and the geographic coordinate grid as the column.

[0072] The vector boundary complexity can be configured according to the number of vertices. The more vertices there are, the higher the vector boundary complexity is, and the greater the corresponding vector boundary complexity weight is.

[0073] The viewing distance can be determined based on the real-time viewing data; the closer the distance, the greater the weight of the viewing distance.

[0074] Therefore: Rendering weight = α * View distance weight + β * Vector boundary complexity weight + γ * Overall popularity score.

[0075] Furthermore, multi-level detail asynchronous loading can be performed on each sub-region in the redline panorama based on the calculated rendering weights.

[0076] The above embodiments highlight high-demand areas and ensure that the core areas most important to users always maintain the highest clarity and zero latency under limited bandwidth, thus solving the problem of critical data loading lag when accessing large-scale resources concurrently.

[0077] S15, when a resource transfer event query instruction triggered based on a target sub-region in the target region is detected, resource transfer information is obtained.

[0078] For example, clients can establish long-lived connections with servers via WebSocket and subscribe to resource flow events, such as land transaction events.

[0079] Furthermore, when a resource transfer event is detected and a corresponding resource transfer event query instruction is received, the transfer timestamp and latest price at the time the resource transfer event occurred can be obtained as the resource transfer information.

[0080] In this embodiment, after a resource transfer event occurs, a transaction snapshot can be generated and stored on the blockchain through hash calculation to prevent data tampering.

[0081] S16, based on the resource flow information and the nonlinear mapping model, the target sub-region is interactively rendered to obtain an interactive panoramic view of resource flow.

[0082] In this embodiment, the step of interactively rendering the target sub-region based on the resource flow information and the nonlinear mapping model to obtain an interactive panoramic view of resource flow includes: Obtain the current timestamp, and obtain the timestamp of the resource transfer event when it occurred from the resource transfer information; Calculate the current network latency; The current timestamp is corrected based on the current network latency to obtain a clock synchronized with the current transfer timestamp; Generate tags based on the resource flow information; Under the clock, the centroid geographic coordinates of the target sub-region are converted into pixel coordinates of the redline panoramic image using the nonlinear mapping model, and the label is dynamically rendered at the position corresponding to the centroid geographic coordinates to obtain the interactive resource flow panoramic view.

[0083] The network latency can be calculated using the NTP (Network Time Protocol) bidirectional timestamp method.

[0084] Furthermore, the clock offset between the client and the server, i.e. the deviation of the local clock from the authoritative time, can be determined based on the network latency, and the current timestamp can be corrected based on the clock offset to obtain a clock synchronized with the flowing timestamp.

[0085] For example, when a user clicks on a specified plot of land, the system can display various information about the resource transfer event that has occurred (such as transfer timestamp, latest price, target sub-region coordinates, transaction location, etc.) and the corresponding tags.

[0086] The above embodiments can solve the data latency problem under high-concurrency bidding, and can simultaneously display the latest transfer status of land parcels for user reference.

[0087] As can be seen from the above technical solutions, this invention can reconstruct the spatial coordinate system of the UAV panoramic dome image based on the surveying vector data, solving the problem of visual displacement between the virtual red line and the real-world features during 360° rotation; it performs attitude compensation rendering on the reconstructed dome image based on real-time perspective data and a nonlinear mapping model, ensuring that the red line always conforms to the real-world terrain without floating; it uses pixel-by-pixel depth mapping to perform occlusion removal processing on the dynamic red line layer, and then combines the occlusion-removed dynamic red line layer with the reconstructed dome image, enabling the red line to be deeply embedded in the real-world scene, significantly enhancing the visual realism; and it performs interactive rendering of the target sub-region based on resource flow information and a nonlinear mapping model, thereby achieving an interactive panoramic display of resource flow information.

[0088] like Figure 2 The diagram shown is a functional block diagram of a preferred embodiment of the rendering apparatus 11 based on the panoramic view resource service engine of the present invention. The rendering apparatus 11 based on the panoramic view resource service engine includes an acquisition unit 110, a reconstruction unit 111, a rendering unit 112, a generation unit 113, a compositing unit 114, and an acquisition unit 115. The module / unit referred to in this invention refers to a series of computer program segments that can be executed by a processor and perform a fixed function, and which are stored in memory. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0089] The acquisition unit 110 is used to acquire mapping vector data of the target area and panoramic dome images of the UAV. The reconstruction unit 111 is used to reconstruct the spatial coordinate system of the UAV panoramic dome image based on the mapping vector data, to obtain the reconstructed dome image and nonlinear mapping model, and to render the reconstructed dome image to the target platform connected to the panoramic viewing resource service engine. The rendering unit 112 is used to collect real-time view data of the user on the target platform through the client, and perform attitude compensation rendering on the reconstructed dome image according to the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view. The generation unit 113 is used to generate a pixel-by-pixel depth map of the reconstructed dome image; The compositing unit 114 is used to perform occlusion removal processing on the dynamic red line layer using the pixel-by-pixel depth mapping, and to perform layer compositing of the dynamic red line layer after occlusion removal processing with the reconstructed dome image to obtain a red line panoramic image. The acquisition unit 115 is used to acquire resource flow information when it receives a resource flow event triggered based on a target sub-region in the target region; The rendering unit 112 is also used to interactively render the target sub-region based on the resource flow information and the nonlinear mapping model to obtain an interactive panoramic view of resource flow.

[0090] As can be seen from the above technical solutions, this invention can reconstruct the spatial coordinate system of the UAV panoramic dome image based on the surveying vector data, solving the problem of visual displacement between the virtual red line and the real-world features during 360° rotation; it performs attitude compensation rendering on the reconstructed dome image based on real-time perspective data and a nonlinear mapping model, ensuring that the red line always conforms to the real-world terrain without floating; it uses pixel-by-pixel depth mapping to perform occlusion removal processing on the dynamic red line layer, and then combines the occlusion-removed dynamic red line layer with the reconstructed dome image, enabling the red line to be deeply embedded in the real-world scene, significantly enhancing the visual realism; and it performs interactive rendering of the target sub-region based on resource flow information and a nonlinear mapping model, thereby achieving an interactive panoramic display of resource flow information.

[0091] like Figure 3 The diagram shown is a structural schematic of a computer device that implements a preferred embodiment of the rendering method based on a panoramic view resource service engine according to the present invention.

[0092] The computer device 1 may include a memory 12, a processor 13, and a bus (the arrow in the figure represents the bus), and may also include a computer program stored in the memory 12 and capable of running on the processor 13, such as a rendering program based on a panoramic view resource service engine.

[0093] Those skilled in the art will understand that the schematic diagram is merely an example of computer device 1 and does not constitute a limitation on computer device 1. Computer device 1 can be either a bus topology or a star topology. Computer device 1 may also include more or fewer other hardware or software than shown in the diagram, or different component arrangements. For example, computer device 1 may also include input / output devices, network access devices, etc.

[0094] It should be noted that the computer device 1 described is merely an example. Other existing or future electronic products that are adaptable to this invention should also be included within the scope of protection of this invention and are incorporated herein by reference.

[0095] The memory 12 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the computer device 1, such as a portable hard drive of the computer device 1. In other embodiments, the memory 12 can be an external storage device of the computer device 1, such as a plug-in portable hard drive, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the computer device 1. Furthermore, the memory 12 can include both internal and external storage units of the computer device 1. The memory 12 can be used not only to store application software and various types of data installed on the computer device 1, such as the code of a rendering program based on a panoramic view resource service engine, but also to temporarily store data that has been output or will be output.

[0096] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the computer device 1, connecting various components of the computer device 1 via various interfaces and lines. It executes programs or modules stored in the memory 12 (e.g., executing rendering programs based on a panoramic resource service engine) and calls data stored in the memory 12 to perform various functions of the computer device 1 and process data.

[0097] The processor 13 executes the operating system of the computer device 1 and various installed applications. The processor 13 executes these applications to implement the steps in the various rendering method embodiments based on the panoramic view resource service engine described above, for example... Figure 1 The steps are shown.

[0098] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete the present invention. The one or more modules / units may be a series of computer-readable instruction segments capable of performing specific functions, which describe the execution process of the computer program in the computer device 1. For example, the computer program may be divided into an acquisition unit 110, a reconstruction unit 111, a rendering unit 112, a generation unit 113, a compositing unit 114, and an acquisition unit 115.

[0099] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium. This software functional module, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute portions of the rendering method based on the panoramic view resource service engine described in the various embodiments of this invention.

[0100] If the modules / units integrated in the computer device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware devices. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above.

[0101] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, etc.

[0102] Furthermore, the computer-readable storage medium may primarily include a stored program area and a stored data area, wherein the stored program area may store the operating system, an application program required for at least one function, etc.; and the stored data area may store data created based on the use of blockchain nodes, etc.

[0103] The blockchain referred to in this invention is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.

[0104] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, in... Figure 3 The bus is represented by only one straight line, but this does not mean that there is only one bus or one type of bus. The bus is configured to enable communication between the memory 12 and at least one processor 13, etc.

[0105] Although not shown, the computer device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 13 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The computer device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0106] Furthermore, the computer device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish a communication connection between the computer device 1 and other computer devices.

[0107] Optionally, the computer device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the computer device 1 and to display a visual user interface.

[0108] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0109] It will be understood by those skilled in the art that Figure 3 The structure shown does not constitute a limitation on the computer device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0110] Combination Figure 1 The memory 12 in the computer device 1 stores multiple instructions to implement a rendering method based on a panoramic view resource service engine, and the processor 13 can execute the multiple instructions to achieve the following: Collect mapping vector data and UAV panoramic dome images of the target area; Based on the mapping vector data, the spatial coordinate system of the UAV panoramic dome image is reconstructed to obtain the reconstructed dome image and nonlinear mapping model, and the reconstructed dome image is rendered to the target platform connected to the panoramic viewing resource service engine. The client collects real-time view data of users on the target platform, and performs attitude compensation rendering on the reconstructed dome image based on the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view. Generate a pixel-by-pixel depth map of the reconstructed dome image; The dynamic red line layer is occluded and culled using the pixel-by-pixel depth mapping, and the occluded and culled dynamic red line layer is then combined with the reconstructed dome image to obtain a panoramic red line image. When a resource transfer event query command triggered based on a target sub-region in the target region is detected, resource transfer information is obtained; Based on the resource flow information and the nonlinear mapping model, the target sub-region is interactively rendered to obtain an interactive panoramic view of resource flow.

[0111] Specifically, the processor 13's implementation method for the above instructions can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0112] It should be noted that all the data involved in this case was legally obtained.

[0113] If any AI models, software tools, or components not belonging to this company appear in the embodiments of this invention, they are merely illustrative examples and do not represent actual use. All user personal information involved in the embodiments of this invention has been obtained by an entity authorized (with the knowledge and consent) or fully authorized by all parties through various legal and compliant means. The collection, storage, use, processing, transmission, provision, and disclosure of the information, data, and signals involved all comply with relevant laws and regulations and do not violate public order and good morals.

[0114] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0115] This invention can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0116] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0117] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0118] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0119] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0120] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices described in this invention can also be implemented by a single unit or device through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A rendering method based on a panoramic look resource service engine, characterized in that, The rendering method based on the panoramic resource service engine includes: Collect mapping vector data and UAV panoramic dome images of the target area; Based on the mapping vector data, the spatial coordinate system of the UAV panoramic dome image is reconstructed to obtain the reconstructed dome image and nonlinear mapping model, and the reconstructed dome image is rendered to the target platform connected to the panoramic viewing resource service engine. The client collects real-time view data of users on the target platform, and performs attitude compensation rendering on the reconstructed dome image based on the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view. Generate a pixel-by-pixel depth map of the reconstructed dome image; The dynamic red line layer is occluded and culled using the pixel-by-pixel depth mapping, and the occluded and culled dynamic red line layer is then combined with the reconstructed dome image to obtain a panoramic red line image. When a resource transfer event query command triggered based on a target sub-region in the target region is detected, resource transfer information is obtained; Based on the resource flow information and the nonlinear mapping model, the target sub-region is interactively rendered to obtain an interactive panoramic view of resource flow.

2. The rendering method based on a panoramic resource service engine as described in claim 1, characterized in that, The step of reconstructing the spatial coordinate system of the UAV panoramic dome image based on the surveying vector data to obtain the reconstructed dome image and nonlinear mapping model includes: Identify ground feature points in the panoramic dome image of the UAV and extract the pixel coordinates of each ground feature point; Obtain the corresponding feature points for each ground feature point from the mapping vector data, and extract the geographic coordinates of each corresponding feature point; Construct control point pairs based on the pixel coordinates of each ground feature point and the geographic coordinates of each feature point with the same name; Initialize the parameters of the panoramic projection spherical model, and use the reprojection error of the control point pair as the objective function to iteratively solve the parameters of the panoramic projection spherical model using the Levenberg-Marquardt method; Construct the nonlinear mapping model based on the optimal parameters obtained from the solution; The spatial coordinate system of the UAV panoramic dome image is reconstructed using the nonlinear mapping model to obtain the reconstructed dome image.

3. The rendering method based on a panoramic resource service engine as described in claim 1, characterized in that, The step of performing attitude compensation rendering on the reconstructed dome image based on the real-time viewpoint data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the viewpoint includes: Identify the redline polygons of each sub-region in the mapping vector data, and obtain the geographic coordinates of each vertex of each redline polygon; The geographic coordinates of each vertex are mapped to spherical coordinates using the nonlinear mapping model, and the spherical coordinates obtained after mapping are inversely calculated based on the real-time view data to obtain the dynamic redline layer.

4. The rendering method based on a panoramic resource service engine as described in claim 1, characterized in that, The step of using the pixel-by-pixel depth map to perform occlusion removal processing on the dynamic red line layer includes: Traverse each red line pixel in the dynamic red line layer and query the depth corresponding to each red line pixel in the pixel-by-pixel depth map to obtain the depth of each red line. Semantic segmentation is performed on the reconstructed dome image to obtain the occlusion mask; Obtain each occlusion pixel in the occlusion mask, and query the depth corresponding to each occlusion pixel in the pixel-by-pixel depth map to obtain the depth of each occlusion. When a first red line depth is detected that is greater than the corresponding first occlusion depth, and the absolute difference between the first red line depth and the first occlusion depth is greater than or equal to a preset threshold, the red line pixel corresponding to the first red line depth is removed from the dynamic red line layer.

5. The rendering method based on a panoramic resource service engine as described in claim 4, characterized in that, The process of combining the dynamic redline layer after occlusion removal processing with the reconstructed dome image to obtain the redline panoramic image includes: The dynamic redline layer after occlusion removal is superimposed on the reconstructed dome image layer by layer according to the hierarchical relationship on the Z-axis to obtain the redline panoramic image. Specifically, when a second red line depth is detected to be greater than the corresponding second occlusion depth and the absolute difference between the second red line depth and the second occlusion depth is less than the preset threshold, and / or the sub-region corresponding to the second red line depth is a high-priority region, the transparency is configured according to the absolute difference; and the red line pixels corresponding to the second red line depth are rendered semi-transparently to the reconstructed dome image according to the transparency. The transparency decreases as the absolute difference increases.

6. The rendering method based on a panoramic resource service engine as described in claim 1, characterized in that, After obtaining the panoramic image of the red line, the method further includes: The flow heat data of each sub-region in the target region is detected, and a resource heat matrix is ​​constructed based on the flow heat data; Calculate the vector boundary complexity for each sub-region; The rendering weight of each sub-region is calculated based on the resource heat matrix, the real-time view data, and the vector boundary complexity. Based on the rendering weights, perform asynchronous loading of multiple levels of detail for each sub-region in the redline panorama.

7. The rendering method based on a panoramic resource service engine as described in claim 1, characterized in that, The step of interactively rendering the target sub-region based on the resource flow information and the nonlinear mapping model to obtain an interactive panoramic view of resource flow includes: Obtain the current timestamp, and obtain the timestamp of the resource transfer event when it occurred from the resource transfer information; Calculate the current network latency; The current timestamp is corrected based on the current network latency to obtain a clock synchronized with the current transfer timestamp; Generate tags based on the resource flow information; Under the clock, the centroid geographic coordinates of the target sub-region are converted into pixel coordinates of the redline panoramic image using the nonlinear mapping model, and the label is dynamically rendered at the position corresponding to the centroid geographic coordinates to obtain the interactive resource flow panoramic view.

8. A rendering device based on a panoramic resource service engine, characterized in that, The rendering device based on the panoramic resource service engine includes: The acquisition unit is used to acquire mapping vector data and UAV panoramic dome images of the target area. The reconstruction unit is used to reconstruct the spatial coordinate system of the UAV panoramic dome image based on the mapping vector data, obtain the reconstructed dome image and nonlinear mapping model, and render the reconstructed dome image to the target platform connected to the panoramic viewing resource service engine. The rendering unit is used to collect real-time view data of users on the target platform through the client, and perform attitude compensation rendering on the reconstructed dome image according to the real-time view data and the nonlinear mapping model to obtain a dynamic redline layer that changes with the view. A generation unit is used to generate a pixel-by-pixel depth map of the reconstructed dome image; The compositing unit is used to perform occlusion removal processing on the dynamic red line layer using the pixel-by-pixel depth mapping, and to perform layer compositing of the dynamic red line layer after occlusion removal processing with the reconstructed dome image to obtain a red line panoramic image. The acquisition unit is used to acquire resource flow information when it receives a resource flow event triggered based on a target sub-region in the target region; The rendering unit is also used to interactively render the target sub-region based on the resource flow information and the nonlinear mapping model to obtain an interactive panoramic view of resource flow.

9. A computer device, characterized in that, The computer device includes: A memory for storing at least one instruction; and a processor for executing the instructions stored in the memory to implement the rendering method based on the panoramic view resource service engine as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, which is executed by a processor in a computer device to implement the rendering method based on the panoramic view resource service engine as described in any one of claims 1 to 7.

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