Method and device for constructing fixed asset map, and electronic device

Abstract

Embodiments of the present application provide a fixed asset map construction method and device and electronic equipment, the method comprising obtaining geographical environment data of a first region; wherein the first region is a region where a fixed asset is located; constructing a first real scene three-dimensional data base of the first region according to the geographical environment data of the first region; obtaining indoor and outdoor three-dimensional laser point clouds and texture image data of a building in the first region; on the first real scene three-dimensional data base, constructing indoor and outdoor of a corresponding building in the first real scene three-dimensional data base according to the indoor and outdoor three-dimensional laser point clouds and texture image data of the building in the first region, to obtain a second real scene three-dimensional data base of the first region; associating attribute information of the fixed asset with the corresponding fixed asset in the second real scene three-dimensional data base, to obtain a map of the fixed asset. The method can improve the intuitiveness and readability of the expression of the fixed asset, and improve the accuracy and efficiency of the fixed asset statistics.

Description

Technical Field

[0001] This application relates to the field of digital information technology, and more specifically, to a method and apparatus for constructing a fixed asset map, and an electronic device. Background Technology

[0002] Fixed assets refer to tangible assets held by an enterprise for the purpose of producing goods, providing services, or managing operations. Examples include factory buildings, machinery and equipment, transportation equipment, and electronic equipment.

[0003] Typically, fixed assets are statistically analyzed using tables. However, using tables to indicate fixed assets makes the representation of fixed assets less intuitive and less readable. Furthermore, since table-based statistics are mainly completed by staff, they are susceptible to human error, and inconsistencies in the tables provided by staff from different departments lead to increased statistical errors and low efficiency. In addition, the wide distribution of fixed assets further complicates the statistical analysis. Summary of the Invention

[0004] This application provides a method, apparatus, and electronic device for constructing a fixed asset map. The map can be used to statistically analyze fixed assets, improving the intuitiveness and readability of fixed asset representation, as well as enhancing the accuracy and efficiency of fixed asset statistics and reducing the difficulty of fixed asset statistics.

[0005] In a first aspect, embodiments of this application provide a method for constructing a fixed asset map, comprising: obtaining geographic environment data of a first region; wherein the first region is the region where the fixed asset is located; constructing a first real-scene 3D data base for the first region based on the geographic environment data of the first region; obtaining indoor and outdoor 3D laser point cloud and texture image data of buildings in the first region; constructing the indoor and outdoor areas of corresponding buildings in the first real-scene 3D data base based on the indoor and outdoor 3D laser point cloud and texture image data of buildings in the first region to obtain a second real-scene 3D data base for the first region; associating the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base to obtain a map of the fixed asset.

[0006] In one possible implementation, the geographic environment data of the first region includes image data, positioning and orientation system data, and image control results of the first region. The step of constructing a first real-scene 3D data base for the first region based on the geographic environment data of the first region includes: extracting feature points from the image data of the first region to obtain feature points for each image of the first region; determining corresponding feature points among different images of the first region based on the feature points of each image of the first region; determining the exterior orientation elements of each image of the first region based on the corresponding feature points among different images of the first region, the positioning and orientation system data of the first region, and the image control results; matching each pixel on each image of the first region based on the exterior orientation elements of each image of the first region to calculate the 3D spatial coordinates of each pixel on each image of the first region; constructing an irregular triangular mesh model of the first region based on the 3D spatial coordinates of each pixel on each image of the first region; matching the image data of the first region with the irregular triangular mesh model, and mapping the texture information of the image data of the first region onto the surface of the irregular triangular mesh model to obtain the first real-scene 3D data base for the first region.

[0007] In one possible implementation, the step of constructing the interior and exterior of the corresponding buildings in the first real-scene 3D data base on the first real-scene 3D data base based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first area to obtain the second real-scene 3D data base for the first area includes: based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first area, combined with real-time localization and mapping (SLAM) technology and refined modeling technology, jointly constructing the interior and exterior of the corresponding buildings in the first real-scene 3D data base on the first real-scene 3D data base to obtain the second real-scene 3D data base for the first area.

[0008] In one possible implementation, associating the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base to obtain a map of the fixed asset includes: determining a first two-dimensional vector surface base map of the first region based on the model bottom outline of the fixed asset in the second real-scene 3D data base map; wherein the first two-dimensional vector surface base map includes multiple vector surfaces, each of the multiple vector surfaces corresponding to one fixed asset; marking the attribute information of the corresponding fixed asset on each vector surface of the first two-dimensional vector surface base map to obtain a second two-dimensional vector surface base map; and associating the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base map by establishing a mapping relationship between the second two-dimensional vector surface base map and the same fixed asset in the second real-scene 3D data base map.

[0009] In one possible implementation, the method further includes: publishing the second two-dimensional vector surface base map and the second real-scene three-dimensional data base as a service to provide services for the related business of the fixed asset.

[0010] In one possible implementation, the method further includes: obtaining basic data of the fixed assets and performing layer management on the basic data of the fixed assets; and configuring different operation permissions for different managers according to the ownership of the fixed assets.

[0011] Secondly, embodiments of this application provide a fixed asset map construction apparatus, comprising: a first obtaining module, configured to obtain geographic environment data of a first region; wherein the first region is the region where the fixed asset is located; a first construction module, configured to construct a first real-scene 3D data base of the first region based on the geographic environment data of the first region; a second obtaining module, configured to obtain indoor and outdoor 3D laser point cloud and texture image data of buildings in the first region; a second construction module, configured to construct the indoor and outdoor areas of corresponding buildings in the first real-scene 3D data base based on the indoor and outdoor 3D laser point cloud and texture image data of buildings in the first region, thereby obtaining a second real-scene 3D data base of the first region; and an association module, configured to associate the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base, thereby obtaining a map of the fixed asset.

[0012] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor; the memory is used to store a computer program; the processor is used to implement the method for constructing a fixed asset map as described in the first aspect when the computer program is executed.

[0013] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for constructing a fixed asset map as described in the first aspect.

[0014] Fifthly, embodiments of this application provide a computer program product that stores computer instructions, which, when executed on a processor, cause the processor to perform the fixed asset map construction method described in any one of the first aspects.

[0015] The beneficial effects of the fixed asset map construction method in this application embodiment are:

[0016] Since the first region is where the fixed assets are located, constructing the first real-scene 3D data base of the first region based on the geographical environment data of the first region can be understood as constructing the geographical environment data of the region where the fixed assets are located, providing a geographical environment data foundation for constructing the map of the fixed assets.

[0017] Furthermore, by constructing the interior and exterior scenes of corresponding buildings in the first real-scene 3D data base based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first area, a second real-scene 3D data base for the first area is obtained. In other words, based on the geographic environment data of the area where the fixed asset is located, the interior and exterior scenes of buildings in that area are constructed, making the second real-scene 3D data base more complete and accurate in reflecting the geographic environment data and interior and exterior scenes of the buildings in the area where the fixed asset is located. This allows the second real-scene 3D data base to comprehensively and accurately reflect the location and status of the fixed asset, providing more complete and accurate data for constructing a map of the fixed asset, thereby improving the accuracy and completeness of the map construction. Thus, by associating the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base, a map of the fixed asset can be obtained. This not only realizes the correspondence and association between the attribute information of the fixed asset and the corresponding fixed asset in the map, but also provides a way to statistically analyze the fixed asset through the map, improving the accuracy of fixed asset statistics.

[0018] Furthermore, a fixed asset map can intuitively indicate the location of fixed assets, their environment and status, as well as their corresponding attribute information. Therefore, a fixed asset map can more intuitively and visually represent fixed assets, improving the intuitiveness and readability of the representation.

[0019] Furthermore, since the process of constructing the fixed asset map is carried out by equipment, it reduces manual input, minimizes human interference, improves the efficiency and labor cost of fixed asset statistics, and further improves the accuracy of fixed asset statistics.

[0020] Furthermore, since the data for constructing the map of fixed assets includes geographical environmental data of the area where the fixed assets are located and 3D laser point cloud and texture image data of the building's interior and exterior, and the above data is collected by unmanned oblique photography equipment and handheld 3D laser scanners, the difficulty of fixed asset statistics is reduced. Attached Figure Description

[0021] Figure 1 A flowchart illustrating a method for constructing a fixed asset map, as provided in an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of the process for constructing a first real-scene 3D data base provided in an embodiment of this application;

[0023] Figure 3 A schematic diagram of a fixed asset map construction apparatus provided in this application embodiment;

[0024] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0026] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0027] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0028] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0029] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0030] Fixed assets refer to tangible assets held by an enterprise for the purpose of producing goods, providing services, or managing operations. For example, for the railway sector, fixed assets mainly include tracks, office buildings, equipment in office buildings, and railway infrastructure along the tracks. As another example, for a property management company, fixed assets mainly include buildings in the residential community, public facilities, trees, roads, and computers, desks, and chairs in the property management office.

[0031] Currently, in order to effectively utilize fixed assets, it is necessary to optimize and integrate them. The prerequisite for optimizing and integrating fixed assets is to conduct asset statistics; clearly, asset statistics are an important task.

[0032] Typically, fixed assets are statistically analyzed using tables. However, using tables to indicate fixed assets makes the representation of assets less intuitive and less readable. Furthermore, since table-based statistics are mainly completed by staff, they are susceptible to human error, and inconsistencies in the tables provided by staff from different departments increase statistical errors and reduce efficiency. In addition, the dispersed distribution of fixed assets further complicates the statistical analysis.

[0033] For example, currently, railway departments are focusing on optimizing, integrating, and sharing their business systems, aiming to improve the quality of information system construction, promote the deep application of information technology in daily work, and ultimately form an intensive development model. The prerequisite for achieving this optimization, integration, and sharing of business systems is to conduct a comprehensive inventory of existing railway-related fixed assets.

[0034] Railway marshalling yards are a type of fixed asset, playing a crucial role in the entire railway transportation system. They undertake a series of key tasks, including vehicle marshalling, cargo loading and unloading, and train dispatching. However, due to the early construction of some railway marshalling yards, numerous management problems exist, leading to the following issues in the statistics of fixed assets within railway marshalling yards: the wide distribution of fixed assets increases the difficulty of statistics; furthermore, the lack of standardized statistical forms results in increased statistical errors and low efficiency.

[0035] In view of this, embodiments of this application provide a method for constructing a fixed asset map, which can be executed by an electronic device. The electronic device includes, but is not limited to, laptops, desktop computers, tablets, etc. Through this method of constructing a fixed asset map, fixed assets can be statistically analyzed using the map, improving the intuitiveness and readability of fixed asset representation, enhancing the accuracy and efficiency of fixed asset statistics, and reducing the difficulty of fixed asset statistics.

[0036] Below, refer to Figure 1 The method for constructing a fixed asset map provided in the embodiments of this application will be described in detail. For example... Figure 1 As shown, the method for constructing this fixed asset map may include:

[0037] 101. Obtain the geographical environment data of the first region.

[0038] The first area is where the fixed assets are located. Fixed assets have already been explained above and will not be repeated here.

[0039] Aerial photography of the first area can be conducted using drone-based oblique photography equipment to obtain geographical environmental data of the first area.

[0040] The geographic environment data for the first region includes, but is not limited to, imagery data, positioning and orientation system data (POS data), and image control results for the first region. Among these:

[0041] The image data for the first area includes, but is not limited to, multi-angle images of the first area.

[0042] The positioning and orientation system data includes relevant data used to determine the position and orientation of each object in the first region in space.

[0043] Image control results mainly refer to the data obtained by measuring image control points. Image control results may include, but are not limited to, the plane coordinates and elevation data of image control points.

[0044] 102. Construct the first real-scene 3D data base of the first region based on the geographical environment data of the first region.

[0045] For example, when the geographic environment data of the first area includes imagery data of the first area, positioning and orientation system data, and image control results, such as Figure 2 As shown, the implementation process of 102 may include the following steps:

[0046] 201. Extract feature points from the image data of the first region to obtain the feature points of each image in the first region.

[0047] The image data for the first region includes multiple images, each of which can be understood as a frame. Feature points are special points in the image data that have unique properties and salient features and can represent important information about a local area of ​​the image.

[0048] For example, feature points for each image can be extracted using feature point extraction algorithms. Feature point extraction algorithms include, but are not limited to, SIFT (Scale Invariant Feature Transform) and SURF (Speed-Up Robust Feature Transform).

[0049] 202. Based on the feature points of each image in the first region, determine the same feature points among different images in the first region.

[0050] For example, feature point matching algorithms (such as feature descriptor-based matching algorithms) can be used to identify corresponding feature points between different images.

[0051] 203. Based on the same-name feature points between different images of the first region, the positioning and orientation system data of the first region, and the image control results, determine the exterior orientation elements of each image of the first region.

[0052] Specifically, based on the corresponding feature points between different images in the first region, combined with the positioning and orientation system data and image control results of the first region, algorithms such as bundle adjustment can be used to calculate the exterior orientation elements (position and attitude parameters) of each image. Among them, the exterior orientation elements of the image indicate the position and attitude of the image in space.

[0053] 204. Based on the exterior orientation elements of each image in the first region, match each pixel in each image in the first region to calculate the three-dimensional spatial coordinates of each pixel in each image in the first region.

[0054] Specifically, based on the exterior orientation elements of each image in the first region, and using a dense matching algorithm, each pixel in each image of the first region can be matched to calculate the three-dimensional spatial coordinates of each pixel in each image of the first region.

[0055] Dense matching algorithms include, but are not limited to, semi-global matching (SGM) and patch-based matching. These algorithms calculate the three-dimensional spatial coordinates of each pixel by matching each pixel in the image.

[0056] 205. Construct an irregular triangular mesh model of the first region based on the three-dimensional spatial coordinates of each pixel on each image of the first region.

[0057] Specifically, the pixels in all images of the first region can be divided into blocks based on the three-dimensional spatial coordinates of each pixel in each image of the first region. An irregular triangular mesh model is then constructed based on the three-dimensional spatial coordinates of the divided pixels.

[0058] When constructing irregular triangular mesh models, the Delaunay triangulation algorithm is often used. This algorithm can ensure that the minimum interior angle of the triangle is maximized, thus making the constructed triangular mesh more reasonable.

[0059] 206. Match the image data of the first region with the irregular triangular mesh model, and map the texture information of the image data of the first region onto the surface of the irregular triangular mesh model to obtain the first real-scene 3D data base of the first region.

[0060] Obviously, by constructing the first real-scene 3D data base, the first real-scene 3D data base can carry information such as buildings, structures, roads, green belts, and environment in the first area.

[0061] 103. Obtain indoor and outdoor 3D laser point cloud and texture image data of buildings in the first area.

[0062] For example, three-dimensional point cloud data and texture image data of the interior and exterior of buildings in the first area can be obtained by a three-dimensional laser scanning device.

[0063] 104. On the first real-scene 3D data base, based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first region, the interior and exterior of the corresponding buildings in the first real-scene 3D data base are constructed to obtain the second real-scene 3D data base of the first region. This ensures that the second real-scene 3D data base of the first region not only includes the basic geographic data in the first real-scene 3D data base, but also includes the refined models of the interior and exterior of buildings in the first region.

[0064] Since fixed assets refer to tangible assets held by an enterprise for the production of goods, provision of services, or business management, a second real-scene 3D data base can be constructed using geographic environmental data of the area where the fixed assets are located (i.e., the first area) and 3D laser point cloud and texture image data of the buildings' interior and exterior. This second real-scene 3D data base carries information about the fixed assets and their geographic environment. In other words, the second real-scene 3D data base includes information such as the location, shape, and status of the fixed assets, providing a data foundation for subsequently generating maps of the fixed assets and for statistically analyzing the fixed assets through these maps.

[0065] 105. The attribute information of fixed assets is associated with the corresponding fixed assets in the second real-scene 3D data base to obtain a map of the fixed assets. In other words, the second real-scene 3D data base associated with the attribute information of fixed assets is called the fixed asset map. The attribute information of fixed assets includes, but is not limited to, the name, number, location, status, age, original value, commissioning time, and net value of the fixed assets. This fixed asset map allows users to intuitively and quickly view fixed assets and their attribute information.

[0066] In summary, since the first region is where the fixed assets are located, constructing the first real-scene 3D data base of the first region based on the geographical environment data of the first region can be understood as constructing the geographical environment data of the region where the fixed assets are located, thus providing a geographical environment data foundation for constructing a map of the fixed assets.

[0067] Furthermore, by constructing the interior and exterior scenes of corresponding buildings in the first real-scene 3D data base based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first area, a second real-scene 3D data base for the first area is obtained. In other words, based on the geographic environment data of the area where the fixed asset is located, the interior and exterior scenes of buildings in that area are constructed, making the second real-scene 3D data base more complete and accurate in reflecting the geographic environment data and interior and exterior scenes of the buildings in the area where the fixed asset is located. This allows the second real-scene 3D data base to comprehensively and accurately reflect the location and status of the fixed asset, providing more complete and accurate data for constructing a map of the fixed asset, thereby improving the accuracy and completeness of the map construction. Thus, by associating the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base, a map of the fixed asset can be obtained. This not only realizes the correspondence and association between the attribute information of the fixed asset and the corresponding fixed asset in the map, but also provides a way to statistically analyze the fixed asset through the map, improving the accuracy of fixed asset statistics.

[0068] Furthermore, a fixed asset map can intuitively indicate the location of fixed assets, their environment and status, as well as their corresponding attribute information. Therefore, a fixed asset map can more intuitively and visually represent fixed assets, improving the intuitiveness and readability of the representation.

[0069] Furthermore, since the process of constructing the fixed asset map is carried out by equipment, it reduces manual input, minimizes human interference, improves the efficiency and labor cost of fixed asset statistics, and further improves the accuracy of fixed asset statistics.

[0070] Furthermore, since the data for constructing the map of fixed assets includes geographical environmental data of the area where the fixed assets are located and 3D laser point cloud and texture image data of the building's interior and exterior, and the above data is collected by UAV oblique photography equipment and handheld 3D laser scanners, the difficulty of fixed asset statistics is reduced.

[0071] In one possible implementation, on a first real-scene 3D data base, the interior and exterior of corresponding buildings in the first real-scene 3D data base are constructed based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first region, to obtain a second real-scene 3D data base for the first region, which may include:

[0072] Based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first area, combined with SLAM (real-time localization and mapping) technology and refined modeling technology, the interior and exterior of the corresponding buildings in the first real-scene 3D data base are jointly constructed on the first real-scene 3D data base to obtain the second real-scene 3D data base of the first area.

[0073] Clearly, joint modeling can improve the accuracy of the construction, thereby further enhancing the accuracy and precision of the second real-scene 3D data base.

[0074] In one possible implementation, associating the attribute information of fixed assets with the corresponding fixed assets in the second real-scene 3D data base to obtain a map of the fixed assets may include:

[0075] First, the first two-dimensional vector plane base map of the first region is determined based on the bottom outline of the fixed asset model in the second real-scene three-dimensional data base.

[0076] The first two-dimensional vector plane base map includes multiple vector planes, and each vector plane corresponds to a fixed asset.

[0077] Then, the attribute information of the corresponding fixed assets is marked on each vector surface of the first two-dimensional vector plane base map to obtain the second two-dimensional vector plane base map.

[0078] The first two-dimensional vector plane base map that will be labeled with the attribute information of fixed assets is called the second two-dimensional vector plane base map.

[0079] Finally, by establishing a mapping relationship between the second two-dimensional vector plane base map and the same fixed asset in the second real-scene three-dimensional data base, the attribute information of the fixed asset is associated with the corresponding fixed asset in the second real-scene three-dimensional data base.

[0080] In one possible implementation, the method for constructing a fixed asset map may also include:

[0081] The second 2D vector map and the second 3D real-world data base are published as services to provide services for fixed asset-related businesses. These fixed asset-related businesses include, but are not limited to, data querying, statistics, and analysis of fixed assets.

[0082] In one possible implementation, the method for constructing a fixed asset map may also include:

[0083] Obtain basic data on fixed assets and manage this data using layered structures. Assign different access permissions to different managers based on the ownership of the fixed assets.

[0084] The basic data of fixed assets includes, but is not limited to, access information and location information of fixed assets. For example, based on the basic data of fixed assets, different types of basic data are divided into different layers to manage the basic data of fixed assets.

[0085] By configuring different management permissions, the security of information in the fixed asset map can be ensured.

[0086] This application also provides an apparatus for constructing a fixed asset map, such as... Figure 3 As shown, the device 300 may include:

[0087] The first acquisition module 301 is used to acquire geographic environment data of a first region; wherein, the first region is the region where the fixed assets are located;

[0088] The first construction module 302 is used to construct a first real-scene 3D data base for the first region based on the geographic environment data of the first region.

[0089] The second acquisition module 303 is used to acquire indoor and outdoor three-dimensional laser point cloud and texture image data of buildings in the first area;

[0090] The second construction module 304 is used to construct the interior and exterior of the corresponding buildings in the first real-scene 3D data base on the first real-scene 3D data base according to the 3D laser point cloud and texture image data of the interior and exterior of the buildings in the first area, so as to obtain the second real-scene 3D data base of the first area.

[0091] The association module 305 is used to associate the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base to obtain a map of the fixed asset.

[0092] Optionally, the geographic environment data of the first area includes image data, positioning and orientation system data, and image control results of the first area;

[0093] The first construction module 302 is specifically used to extract feature points from the image data of the first region to obtain feature points for each image of the first region; determine corresponding feature points among different images of the first region based on the feature points of each image of the first region; determine the exterior orientation elements of each image of the first region based on the corresponding feature points among different images of the first region, the positioning and orientation system data of the first region, and the image control results; match each pixel on each image of the first region based on the exterior orientation elements of each image of the first region to calculate the three-dimensional spatial coordinates of each pixel on each image of the first region; construct an irregular triangular mesh model of the first region based on the three-dimensional spatial coordinates of each pixel on each image of the first region; match the image data of the first region with the irregular triangular mesh model, and map the texture information of the image data of the first region onto the surface of the irregular triangular mesh model to obtain the first real-scene three-dimensional data base of the first region.

[0094] Optionally, the second construction module 304 is specifically used to, based on the three-dimensional laser point cloud and texture image data of the interior and exterior of the buildings in the first area, and combined with SLAM (real-time localization and mapping) technology and refined modeling technology, jointly construct the interior and exterior of the corresponding buildings in the first real-scene three-dimensional data base on the first real-scene three-dimensional data base to obtain the second real-scene three-dimensional data base of the first area.

[0095] Optionally, the association module 305 is specifically used to determine a first two-dimensional vector surface base map of the first region based on the bottom outline of the model of the fixed asset in the second real-scene 3D data base map; wherein, the first two-dimensional vector surface base map includes multiple vector surfaces, each of the multiple vector surfaces corresponding to one of the fixed assets; the attribute information of the corresponding fixed asset is marked on each vector surface of the first two-dimensional vector surface base map to obtain a second two-dimensional vector surface base map; by establishing a mapping relationship between the second two-dimensional vector surface base map and the same fixed asset in the second real-scene 3D data base map, the attribute information of the fixed asset is associated with the corresponding fixed asset in the second real-scene 3D data base map.

[0096] Optionally, the association module 305 is also used to publish the second two-dimensional vector surface base map and the second real-scene three-dimensional data base as a service to provide services for the related business of the fixed asset.

[0097] Optionally, the association module 305 is also used to obtain the basic data of the fixed assets and perform layer management on the basic data of the fixed assets; and to configure different operation permissions for different managers according to the ownership of the fixed assets.

[0098] like Figure 4 As shown, an electronic device 400 provided in this embodiment of the invention may include a processor 410 and a memory 420; the memory 420 is used to store a computer program; the processor 410 is used to implement the fixed asset map construction method as described above when the computer program is executed.

[0099] This invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the fixed asset map construction method described above.

[0100] This invention provides a computer program product that stores computer instructions. When the computer instructions are executed on a processor, the processor performs the fixed asset map construction method as described above.

[0101] The present invention will now be described an electronic device 400 that can serve as a server or client of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. Electronic device 400 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 400 can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0102] Electronic device 400 includes a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or a computer program loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0103] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units 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 units can be implemented in hardware or as software functional units.

[0104] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for constructing a fixed asset map, characterized in that, include: Obtain the geographical environment data of the first region; wherein, the first region is the region where the fixed assets are located; Construct a first real-scene 3D data base for the first region based on the geographic environment data of the first region; Obtain indoor and outdoor 3D laser point cloud and texture image data of buildings within the first area; On the first real-scene 3D data base, the interior and exterior of the corresponding buildings in the first real-scene 3D data base are constructed based on the 3D laser point cloud and texture image data of the interior and exterior of the buildings in the first area, so as to obtain the second real-scene 3D data base of the first area. The attribute information of the fixed assets is associated with the corresponding fixed assets in the second real-scene 3D data base to obtain a map of the fixed assets. The geographic environment data of the first region includes image data, positioning and orientation system data, and image control results of the first region; The step of constructing the first real-scene 3D data base of the first region based on the geographic environment data of the first region includes: Feature points are extracted from the image data of the first region to obtain the feature points of each image in the first region. Based on the feature points of each image in the first region, identify corresponding feature points among different images in the first region; Based on the same-name feature points between different images of the first region, the positioning and orientation system data of the first region and the image control results, determine the exterior orientation elements of each image of the first region. Based on the exterior orientation elements of each image in the first region, each pixel in each image of the first region is matched to calculate the three-dimensional spatial coordinates of each pixel in each image of the first region. Based on the three-dimensional spatial coordinates of each pixel on each image of the first region, an irregular triangular mesh model of the first region is constructed. The image data of the first region is matched with the irregular triangular mesh model, and the texture information of the image data of the first region is mapped onto the surface of the irregular triangular mesh model to obtain the first real-scene three-dimensional data base of the first region. The step of constructing the interior and exterior of corresponding buildings in the first real-scene 3D data base based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first region on the first real-scene 3D data base to obtain the second real-scene 3D data base of the first region includes: Based on the 3D laser point cloud and texture image data of the interior and exterior of buildings in the first area, combined with real-time positioning and map building technology and refined modeling technology, the interior and exterior of the corresponding buildings in the first real-scene 3D data base are jointly constructed on the first real-scene 3D data base to obtain the second real-scene 3D data base of the first area.

2. The method according to claim 1, characterized in that, The step of associating the attribute information of the fixed assets with the corresponding fixed assets in the second real-scene 3D data base to obtain a map of the fixed assets includes: The first two-dimensional vector plane base map of the first region is determined based on the bottom outline of the model of the fixed asset in the second real-scene three-dimensional data base. The first two-dimensional vector plane base map includes multiple vector planes, and each of the multiple vector planes corresponds to one of the fixed assets; The attribute information of the corresponding fixed assets is marked on each vector surface of the first two-dimensional vector surface base map to obtain the second two-dimensional vector surface base map; By establishing a mapping relationship between the second two-dimensional vector plane base map and the same fixed asset in the second real-scene three-dimensional data base, the attribute information of the fixed asset is associated with the corresponding fixed asset in the second real-scene three-dimensional data base.

3. The method according to claim 2, characterized in that, The method further includes: The second two-dimensional vector surface base map and the second real-scene three-dimensional data base are published as services to provide services for the related business of the fixed assets.

4. The method according to claim 1, characterized in that, The method further includes: Obtain the basic data of the fixed assets and perform layer management on the basic data of the fixed assets; Different operating permissions are configured for different managers based on the ownership of the fixed assets.

5. A device for constructing a fixed asset map, characterized in that, The method for constructing a fixed asset map as described in any one of claims 1 to 4 includes: The first acquisition module is used to acquire geographic environment data of a first region; wherein, the first region is the region where the fixed assets are located; The first construction module is used to construct the first real-scene 3D data base of the first region based on the geographic environment data of the first region. The second acquisition module is used to acquire indoor and outdoor three-dimensional laser point cloud and texture image data of buildings in the first area; The second construction module is used to construct the interior and exterior of the corresponding buildings in the first real-scene 3D data base on the first real-scene 3D data base according to the 3D laser point cloud and texture image data of the interior and exterior of the buildings in the first area, so as to obtain the second real-scene 3D data base of the first area. The association module is used to associate the attribute information of the fixed asset with the corresponding fixed asset in the second real-scene 3D data base to obtain a map of the fixed asset.

6. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the method for constructing a fixed asset map as described in any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method for constructing a fixed asset map as described in any one of claims 1 to 4.

8. A computer program product, characterized in that, The computer program product stores computer instructions that, when executed on a processor, cause the processor to perform the method for constructing a fixed asset map according to any one of claims 1 to 4.

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