A method, device and electronic device for optimizing loading of oblique photography model data

Abstract

The embodiments of this specification disclose an optimized loading method, device and electronic device for oblique photography model data. The method includes obtaining oblique photography model data and terrain elevation data, determining the longitude and latitude coordinates of the oblique photography model data center point and the terrain height of the model center point, integrating them to obtain the combined center point coordinates, and then respectively determining the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the model center point and the second Cartesian coordinates corresponding to the combined center point coordinates, and converting and loading all oblique photography model data based on the translation matrix to obtain a target conversion photography model. Through the above optimized loading steps, the purpose of automatically adjusting the height position of the model, eliminating the overlap and suspension effects of the terrain elevation data model, and improving the model adjustment efficiency is achieved, and by positioning the real terrain height of the model center point, the fitting effect of the adjusted model and the real surface is improved.

Description

Technical Field

[0001] One or more embodiments of the present specification relate to the technical field of model data optimization, and in particular, to a method, device and electronic device for optimizing loading of oblique photography model data. Background Art

[0002] With the rapid development of intelligent driving technology, the requirements for terrain display effects of GIS maps are getting higher and higher. In GIS maps, in order to more realistically show the real original terrain information and the 3D effects of each building, it is often necessary to introduce oblique photography model data and terrain elevation data into the GIS map at the same time. However, since the map is attached with the ups and downs of elevation data, if the oblique photography data is not processed during the loading process, it will sink to the bottom of the elevation terrain or hang above the elevation data, and cannot be fully displayed in the map. Therefore, a method is needed to optimize the loading of oblique photography model data, but the current existing optimization methods generally use the loaded model to manually adjust the height position of the model by manual visual judgment. The adjustment efficiency is often low due to the huge adjustment workload, and it is impossible to guarantee the actual fit between the model and the real surface after each adjustment. Summary of the invention

[0003] The embodiments of this specification provide a method, device and electronic device for optimizing loading of oblique photography model data, and the technical solution thereof is as follows:

[0004] In a first aspect, an embodiment of the present specification provides a method for optimizing loading of oblique photography model data, the method comprising:

[0005] Obtain oblique photography model data and terrain elevation data, determine the bounding box range corresponding to the oblique photography model data based on the coordinate maximum method, and determine the longitude and latitude coordinates of the model center point corresponding to the bounding box range;

[0006] Determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method;

[0007] Integrate the latitude and longitude coordinates of the center point of the model and the terrain height of the center point of the model to obtain the coordinates of the combined center point, and determine the first Cartesian coordinates corresponding to the latitude and longitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the coordinates of the combined center point based on the Cartesian coordinate conversion method;

[0008] The translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate is determined based on a three-dimensional space translation method, and all the oblique photography model data are converted and loaded based on the translation matrix to obtain a target conversion photography model.

[0009] In a second aspect, a device for optimizing and loading oblique photography model data is provided, the device comprising:

[0010] An acquisition module, used to acquire oblique photography model data and terrain elevation data, determine the bounding box range corresponding to the oblique photography model data based on the coordinate maximum value method, and determine the longitude and latitude coordinates of the model center point corresponding to the bounding box range;

[0011] A determination module, used to determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on a latitude and longitude format conversion method;

[0012] An integration module is used to integrate the longitude and latitude coordinates of the center point of the model and the terrain height of the center point to obtain the combined coordinates of the center point of the model, and determine the Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the combined coordinates of the center point of the model based on the Cartesian coordinate conversion method to obtain the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the combined coordinates of the center point of the model;

[0013] The loading module is used to determine the translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate based on the three-dimensional space translation method, and to convert and load all the oblique photography model data based on the translation matrix to obtain a target conversion photography model.

[0014] In a third aspect, an electronic device is provided, including a device processor and a memory;

[0015] The device processor is connected to the memory;

[0016] The memory is used to store executable program code;

[0017] The device processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the steps of the method provided in the first aspect or any possible implementation manner of the first aspect.

[0018] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and the computer-readable storage medium stores instructions, which, when the instructions are executed on a computer or a device processor, cause the computer or the device processor to execute the method provided in the first aspect or any possible implementation of the first aspect.

[0019] The beneficial effects brought by the technical solutions provided by some embodiments of this specification include at least:

[0020] In one or more embodiments of the present specification, after obtaining the oblique photography model data and the terrain elevation data, the latitude and longitude coordinates of the model center point corresponding to the bounding box range of the oblique photography model data are determined, and then the terrain height of the model center point is determined based on the terrain height acquisition method, and the latitude and longitude coordinates of the model center point and the terrain height of the model center point are integrated to obtain the combined center point coordinates, and then the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the model center point and the second Cartesian coordinates corresponding to the combined center point coordinates are determined by the Cartesian coordinate conversion method, and all the oblique photography model data are converted and loaded based on the translation matrix corresponding to the first Cartesian coordinates and the second Cartesian coordinates to obtain the target conversion photography model. Through the above optimized loading steps, the purpose of automatically adjusting the height position of the model, eliminating the overlap and suspension effects of the terrain elevation data model, and improving the efficiency of model adjustment is achieved, and the real terrain height positioning of the model center point is improved to improve the fit effect of the adjusted model with the real surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A schematic diagram of the system architecture of an optimized loading method for oblique photography model data provided in an embodiment of this specification;

[0023] Figure 2 A flowchart of an optimized loading method for oblique photography model data provided by an embodiment of this specification;

[0024] Figure 3 A schematic diagram of the structure of an optimized loading device for oblique photography model data provided in an embodiment of this specification;

[0025] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0027] The terms "first", "second", "third", etc. in the description and claims of this specification and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0028] The following description provides examples and does not limit the scope, applicability or examples set forth in the claims. Changes may be made to the functions and arrangements of the elements described without departing from the scope of the present specification. Various processes or components may be appropriately omitted, substituted or added to each example. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted or combined. In addition, features described with respect to some examples may be combined in other examples.

[0029] See also Figure 1 , Figure 1 A schematic diagram of the system architecture of an optimized loading method for oblique photography model data provided in an embodiment of this specification is shown.

[0030] like Figure 1 As shown, the system architecture of the method for optimizing loading of oblique photography model data may include at least a terminal 10 , a server 20 and a network 30 .

[0031] The terminal 10 includes but is not limited to electronic devices such as smart phones, desktop computers, tablet computers, laptops, smart speakers, digital assistants, and smart wearable devices, and may also be software running on the above electronic devices, such as applications. Optionally, the operating system running on the electronic device may include but is not limited to Android, IOS, Linux, Windows, etc. Optionally, the terminal 10 provides an optimized loading service to the user, and the terminal 10 may obtain an optimized loading instruction of an application program interface and send an optimized loading request to the server 20.

[0032] The server 20 can provide background services for the terminal 10. According to the optimization loading request sent by the terminal 10, the server 20 will obtain a series of optimization loading instructions, and the server 20 will transmit the optimization loading instructions to other terminals 10 through the network 30. Specifically, the server 20 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, 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 communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0033] The network 30 is used to provide a medium for a communication link between the terminal 10 and the server 20. The network 30 may include various connection types, such as wired or wireless communication links or optical fiber cables.

[0034] In addition, it should be noted that Figure 1 What is shown is only one system provided by the present disclosure. In practical applications, other systems may also be included, for example, more terminals may be included.

[0035] In the embodiments of the present specification, the terminal 10 and the server 20 may be directly or indirectly connected via wired or wireless communication, which is not limited in the present disclosure.

[0036] See next Figure 2 , Figure 2 The overall flow chart of an optimized loading method of oblique photography model data provided by an embodiment of the present specification is shown. The optimized loading method of oblique photography model data can be used in the server 20.

[0037] like Figure 2 As shown, the optimization loading method of the oblique photography model data may at least include the following steps:

[0038] Step 201: Obtain oblique photography model data and terrain elevation data, determine a bounding box range corresponding to the oblique photography model data based on a coordinate extremum method, and determine the longitude and latitude coordinates of a model center point corresponding to the bounding box range.

[0039] In the embodiment of the present specification, in order to introduce the oblique photography model and terrain elevation data loading scenario into the system at the same time, and to eliminate the model overlap or suspension effect caused by the terrain elevation data as much as possible, the oblique photography model data and the terrain elevation data can be obtained at the same time. Among them, the oblique photography data includes high-resolution image data in five shooting angle directions obtained by shooting the ground from vertical angles and four oblique angles, and the terrain elevation data is a data set of height changes on the earth's surface, including the height value of each point on the earth's surface, which can exist in a raster format (such as DEM) or a vector format (such as contour lines). Then, the coordinate maximum value method is used to determine the maximum coordinate points in each direction of all the oblique photography model data obtained. Outside the oblique photography model, a minimum circumscribed polygon can be set and defined as the bounding box range corresponding to the oblique photography model, and the corresponding bounding box range of the oblique photography model is determined by each maximum coordinate point. Further, the model center point in the bounding box range is determined, and the longitude and latitude coordinates of the corresponding model center point in the bounding box are obtained based on the coordinate point address query and longitude and latitude coordinate conversion.

[0040] Optionally, when determining the bounding box range through the oblique photography model data, the oblique photography model can be first divided into multiple model units, and the unit range corresponding to each model unit can be compared by the coordinate maximum value comparison method, and then the single enclosing range corresponding to each single model unit can be merged through the maximum value coordinates. Alternatively, the oblique photography model data can be set as the model input and the bounding box range as the model output through a machine learning model, and the oblique photography model data can be directly input into the trained machine learning model to directly obtain the bounding box range corresponding to the oblique photography model.

[0041] In one possible implementation, the determining the bounding box range corresponding to the oblique photography model data based on the coordinate extremum method includes:

[0042] Determine at least two model tiles corresponding to the oblique photography model based on the oblique photography model data;

[0043] The single tile range corresponding to each model tile is determined based on the coordinate extremum method, and all the single tile ranges are merged to obtain the bounding box range corresponding to the oblique photography model data.

[0044] In the embodiment of the present specification, a complete 3D oblique photography model can be constructed by first acquiring the oblique photography model data of the five shooting angles, and the oblique photography model can be divided into multiple model tiles, and then the size, complexity and data density of the oblique photography model can be used to determine the number of model tiles to be divided. Then, for each model tile, all the data contained therein can be traversed first, and then the minimum and maximum values ​​in the three directions of the X, Y and Z axes in the 3D model can be calculated by the coordinate extremum method, and an accurate single tile range is defined by the calculated minimum and maximum values, and its boundary is determined by the minimum and maximum values. Further, after calculating the single tile range of all model tiles, by comparing the coordinate extremum of all single tile ranges, taking the minimum and maximum values ​​of each coordinate axis, all single tile ranges are merged to obtain the bounding box range corresponding to all oblique photography model data. As an example, the bounding box range can be a cuboid surrounded by eight vertex coordinates.

[0045] In one possible implementation, determining the longitude and latitude coordinates of the model center point corresponding to the bounding box range includes:

[0046] Determine the model center point corresponding to the bounding box range based on the center point positioning method, and determine the center point data address corresponding to the model center point;

[0047] Determine the longitude and latitude coordinates of the model center point corresponding to the center point data address.

[0048] In the embodiment of the present specification, after determining the bounding box range corresponding to the oblique photography model, the center point positioning method is used to take the average value of the minimum and maximum values ​​of the bounding box on the three coordinate axes of X, Y, and Z to determine the bounding coordinates of the center point of the model in the bounding box coordinate system, wherein the center point of the model is the three-dimensional point coordinate under the 3D oblique photography model coordinate system. When the model data points are structured, each model data point corresponds to an address format data, so the center point data address corresponding to the center point of the model can be determined through the model data storage file. Furthermore, since the center point coordinates contained in the center point data address are calculated in the three-dimensional model coordinate system of the local bounding box, it is necessary to first obtain the latitude and longitude coordinate system origin parameters through the configuration information in the system map, and then convert each address format data into longitude and latitude coordinates. Finally, the center point data address can be queried to obtain the longitude and latitude coordinates of the center point of the model.

[0049] Step 202: Determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method.

[0050] In an embodiment of the present specification, the acquired terrain elevation data is first preprocessed, which may include first converting the format of the terrain elevation data to ensure that the acquired terrain elevation data is in a unified data format, and then calibrating the coordinate system and splicing the data, calibrating all terrain elevation data to a standard terrain coordinate system and splicing discontinuous data to ensure the consistency and availability of the terrain elevation data. Next, the acquired terrain elevation data is used to determine that the terrain height values ​​and the coordinates of each geographical location form a terrain height collection library, and the longitude and latitude coordinates of the model center point are used to find the corresponding geographical location in the terrain height collection library, and extract the terrain height value corresponding to the geographical location. Optionally, the terrain height value can be subjected to data rationalization verification to exclude possible abnormal values ​​and erroneous data. Finally, the terrain height value is determined as the terrain height of the model center point.

[0051] In one possible implementation, the method for determining the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method includes:

[0052] Determine the geographic coordinates corresponding to the longitude and latitude coordinates of the center point of the model based on the longitude and latitude format conversion;

[0053] A terrain database corresponding to the terrain elevation data is determined based on a terrain height acquisition method, and the terrain height of the model center point corresponding to the geographic coordinates is queried in the terrain database.

[0054] In the embodiments of this specification, the calibrated geographic coordinate system can be used as a coordinate conversion reference. Then, since the longitude and latitude coordinates of the center point of the model determine the coordinate position of the center of the model on the surface of the earth by the longitude and latitude values, the longitude and latitude coordinates of the center point of the model can be converted into coordinate format in the calibrated geographic coordinate system by longitude and latitude format conversion, and its two-dimensional longitude and latitude coordinates are converted into three-dimensional geographic coordinates with average altitude. Further, the corresponding terrain database is determined by the acquired terrain elevation data. In the terrain database, each geographic coordinate corresponds to a terrain height. Therefore, a query request corresponding to the geographic coordinate is sent to the terrain database through API calls, direct database queries, or downloading data files of a specific area to obtain the terrain height of the center point of the model corresponding to the geographic coordinate.

[0055] Step 203: Integrate the longitude and latitude coordinates of the model center point and the terrain height of the model center point to obtain the combined center point coordinates, and determine the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the model center point and the second Cartesian coordinates corresponding to the combined center point coordinates based on the Cartesian coordinate conversion method.

[0056] In the embodiment of the present specification, the obtained latitude and longitude coordinates (Latitude, Longitude) of the model center point and the terrain height h of the model center point are first integrated to obtain the combined center point coordinates (Latitude, Longitude, h) required for the subsequent Cartesian coordinate conversion, and the latitude and longitude coordinates (Latitude, Longitude) of the model center point are integrated with the original terrain height h0 to obtain the original combined coordinates (Latitude, Longitude, h0). Then, the Cartesian coordinate conversion method from the geographic coordinate system to the geocentric coordinate system is selected to convert the original combined coordinates and the combined center point coordinates respectively to obtain the first Cartesian coordinates corresponding to the latitude and longitude coordinates of the model center point and the second Cartesian coordinates corresponding to the combined center point coordinates.

[0057] As an example, the first Cartesian coordinate (X1, Y1, Z1) can be obtained using the following formula:

[0058] X1 = (R + h0) * cos(Latitude) * cos(Longitude)

[0059] Y1 = (R + h0) * cos(Latitude) * sin(Longitude)

[0060] Z1 = ((R*(1 - e^2)) + h0) * sin(Latitude) where R is the radius of the earth, h0 is the altitude (0 in this case), e is the eccentricity of the earth, and Latitude and Longitude are the longitude and latitude coordinates in radians.

[0061] By substituting the combined center point coordinates (Latitude, Longitude, h) into the above formula, the second Cartesian coordinates (X2, Y2, Z2) can be obtained.

[0062] In one possible implementation, the determining of the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the coordinates of the combined center point based on the Cartesian coordinate conversion method respectively includes:

[0063] Determine the original center point coordinates corresponding to the latitude and longitude coordinates of the center point of the model;

[0064] Determine coordinate parameters corresponding to the original center point coordinates and the combined center point coordinates respectively, wherein the coordinate parameters include longitude value, latitude value and altitude value;

[0065] Cartesian coordinate transformation is performed on each of the coordinate parameters to obtain a first Cartesian coordinate corresponding to the original center point coordinate and a second Cartesian coordinate corresponding to the combined center point coordinate.

[0066] In the embodiment of the present specification, when the Cartesian coordinate conversion method from the geographic coordinate system to the geocentric coordinate system is selected, the original center point coordinates (Latitude, Longitude, 0) corresponding to the longitude and latitude coordinates (Latitude, Longitude) of the model center point can be determined first, that is, the corresponding original terrain height is set to 0. Then, the longitude value, latitude value and altitude value coordinate parameters corresponding to the original center point coordinates and the longitude value, latitude value and altitude value coordinate parameters corresponding to the combined center point coordinates (Latitude, Longitude, h) are determined. Further, each coordinate parameter is input into the selected Cartesian coordinate conversion formula to obtain the first Cartesian coordinate corresponding to the original center point coordinates and the second Cartesian coordinate corresponding to the combined center point coordinates.

[0067] Step 204: determine the translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate based on the three-dimensional space translation method, and convert and load all the oblique photography model data based on the translation matrix to obtain a target conversion photography model.

[0068] In the embodiment of this specification, after determining the first Cartesian coordinate (X1, Y1, Z1) and the second Cartesian coordinate (X2, Y2, Z2), the coordinate difference (ΔX, ΔY, ΔZ) between the first Cartesian coordinate (X1, Y1, Z1) and the second Cartesian coordinate (X2, Y2, Z2) can be determined by coordinate difference calculation, and then the calculated coordinate difference (ΔX, ΔY, ΔZ) is mapped to the constructed initial translation matrix through the three-dimensional space translation method to obtain the corresponding target translation matrix. Further, all oblique photography model data are converted and loaded using the target translation matrix to ensure that the entire model is translated and updated to the expected overlapping position to obtain the target conversion photography model.

[0069] In one possible implementation, determining the translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate based on the three-dimensional space translation method includes:

[0070] Determine a coordinate difference between the first Cartesian coordinate and the second Cartesian coordinate based on the difference component, and determine a translation component corresponding to the coordinate difference;

[0071] The translation component is mapped into an initial four-dimensional matrix based on a three-dimensional space translation method to obtain a translation matrix.

[0072] In the embodiment of this specification, the first Cartesian coordinate (X1, Y1, Z1) and the second Cartesian coordinate (X2, Y2, Z2) are first determined. Then, the translation component (ΔX, ΔY, ΔZ) between the two coordinates is calculated by the difference component, where ΔX = X2 - X1, ΔY = Y2 - Y1, ΔZ = Z2 - Z1. Then, in three-dimensional space, the translation matrix is ​​a 4x4 matrix, in which the fourth column is the translation component, and the rest is the initial matrix, indicating no rotation or scaling. Constructing an initial four-dimensional matrix is ​​as follows:

[0073]

[0074] Furthermore, the translation component is mapped to the initial four-dimensional matrix through the three-dimensional space translation method, and the translation matrix is ​​obtained as follows:

[0075]

[0076] In one possible implementation, the step of converting and loading all the oblique photography model data based on the translation matrix to obtain a target conversion photography model includes:

[0077] Convert all the oblique photography model data with the translation matrix respectively to obtain terrain height conversion data;

[0078] All the terrain height conversion data are loaded and modeled to obtain a target photography model.

[0079] In the embodiment of this specification, all oblique photography model data are converted and calculated with the translation matrix to obtain the terrain height conversion data. Then, after obtaining the terrain height conversion data corresponding to all oblique photography model data, it is loaded and modeled to obtain the target photography model corresponding to the expected overlap position.

[0080] As an example, the translation matrix T may be in the following form:

[0081]

[0082] Wherein, Δx, Δy, and Δz are coordinate differences calculated between the first Cartesian coordinate and the second Cartesian coordinate, respectively.

[0083] When the translation matrix is ​​used to translate any point P (x, y, z) in the oblique photography model data, the following formula can be used to obtain the translated terrain height conversion data P':

[0084]

[0085] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0086] See next Figure 3 , Figure 3 The schematic diagram of the structure of an optimization loading device for oblique photography model data provided in the embodiment of this specification is shown. It should be noted that: Figure 3 The optimized loading device of the oblique photography model data shown is used to execute the present application Figure 2 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figure 2 The embodiment shown.

[0087] like Figure 3 As shown, the optimization loading device of the oblique photography model data may at least include:

[0088] The acquisition module 301 is used to acquire oblique photography model data and terrain elevation data, determine the bounding box range corresponding to the oblique photography model data based on the coordinate maximum value method, and determine the longitude and latitude coordinates of the model center point corresponding to the bounding box range;

[0089] A determination module 302 is used to determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on a latitude and longitude format conversion method;

[0090] An integration module 303 is used to integrate the longitude and latitude coordinates of the center point of the model and the terrain height of the center point to obtain the combined coordinates of the center point of the model, and determine the Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the combined coordinates of the center point of the model based on a Cartesian coordinate conversion method to obtain the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the combined coordinates of the center point of the model;

[0091] The loading module 304 is used to determine the translation matrix corresponding to the first Cartesian coordinates and the second Cartesian coordinates based on the three-dimensional space translation method, and convert and load all the oblique photography model data based on the translation matrix to obtain a target conversion photography model.

[0092] In one possible implementation, the acquisition module 301 is specifically used for:

[0093] Determine at least two model tiles corresponding to the oblique photography model based on the oblique photography model data;

[0094] The single tile range corresponding to each model tile is determined based on the coordinate extremum method, and all the single tile ranges are merged to obtain the bounding box range corresponding to the oblique photography model data.

[0095] In one possible implementation, the acquisition module 301 is further specifically used for:

[0096] Determine the model center point corresponding to the bounding box range based on the center point positioning method, and determine the center point data address corresponding to the model center point;

[0097] Determine the longitude and latitude coordinates of the model center point corresponding to the center point data address.

[0098] In one possible implementation, the determination module 302 is specifically configured to:

[0099] Determine the geographic coordinates corresponding to the longitude and latitude coordinates of the center point of the model based on the longitude and latitude format conversion;

[0100] A terrain database corresponding to the terrain elevation data is determined based on a terrain height acquisition method, and the terrain height of the model center point corresponding to the geographic coordinates is queried in the terrain database.

[0101] In one possible implementation, the integration module 303 is specifically used for:

[0102] Determine the original center point coordinates corresponding to the latitude and longitude coordinates of the center point of the model;

[0103] Determine coordinate parameters corresponding to the original center point coordinates and the combined center point coordinates respectively, wherein the coordinate parameters include longitude value, latitude value and altitude value;

[0104] Cartesian coordinate transformation is performed on each of the coordinate parameters to obtain a first Cartesian coordinate corresponding to the original center point coordinate and a second Cartesian coordinate corresponding to the combined center point coordinate.

[0105] In one possible implementation, the loading module 304 is specifically used for:

[0106] Determine a coordinate difference between the first Cartesian coordinate and the second Cartesian coordinate based on the difference component, and determine a translation component corresponding to the coordinate difference;

[0107] The translation component is mapped into an initial four-dimensional matrix based on a three-dimensional space translation method to obtain a translation matrix.

[0108] In one possible implementation, the loading module 304 is further used to:

[0109] Convert all the oblique photography model data with the translation matrix respectively to obtain terrain height conversion data;

[0110] All the terrain height conversion data are loaded and modeled to obtain a target photography model.

[0111] Those skilled in the art can clearly understand that the technical solutions of the embodiments of the present application can be implemented with the help of software and / or hardware. The "unit" and "module" in this specification refer to software and / or hardware that can independently complete or cooperate with other components to complete specific functions, where the hardware can be, for example, a field programmable gate array (FPGA), an integrated circuit (IC), etc.

[0112] Each processing unit and / or module of the embodiments of the present application may be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or may be implemented by software that executes the functions described in the embodiments of the present application.

[0113] See next Figure 4 , Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification is shown.

[0114] like Figure 4 As shown, the electronic device 400 may include: at least one device processor 401 , at least one network interface 404 , a user interface 403 , a memory 405 , and at least one communication bus 402 .

[0115] The communication bus 402 may be used to realize the connection and communication among the above-mentioned components.

[0116] The user interface 403 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0117] The network interface 404 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0118] Among them, the device processor 401 may include one or more processing cores. The device processor 401 uses various interfaces and lines to connect various parts within the entire electronic device 400, and executes various functions and processes data of the electronic device 400 by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the device processor 401 can be implemented in at least one hardware form of DSP, FPGA, and PLA. The device processor 401 can integrate one or a combination of CPU, GPU, modem, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to handle wireless communications. It can be understood that the above-mentioned modem may not be integrated into the device processor 401, and it can be implemented separately through a chip.

[0119] The memory 405 may include a RAM or a ROM. Optionally, the memory 405 includes a non-transitory computer-readable medium. The memory 405 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 405 may optionally be at least one storage device located away from the aforementioned device processor 401. As Figure 4 As shown, the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module, and program instructions.

[0120] Specifically, the device processor 401 may be used to call the optimization loading application for the oblique photography model data stored in the memory 405, and specifically perform the following operations:

[0121] Obtain oblique photography model data and terrain elevation data, determine the bounding box range corresponding to the oblique photography model data based on the coordinate maximum method, and determine the longitude and latitude coordinates of the model center point corresponding to the bounding box range;

[0122] Determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method;

[0123] Integrate the latitude and longitude coordinates of the center point of the model and the terrain height of the center point of the model to obtain the coordinates of the combined center point, and determine the first Cartesian coordinates corresponding to the latitude and longitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the coordinates of the combined center point based on the Cartesian coordinate conversion method;

[0124] The translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate is determined based on a three-dimensional space translation method, and all the oblique photography model data are converted and loaded based on the translation matrix to obtain a target conversion photography model.

[0125] As an optional embodiment of the present specification, the determining the bounding box range corresponding to the oblique photography model data based on the coordinate maximum method includes:

[0126] Determine at least two model tiles corresponding to the oblique photography model based on the oblique photography model data;

[0127] The single tile range corresponding to each model tile is determined based on the coordinate extremum method, and all the single tile ranges are merged to obtain the bounding box range corresponding to the oblique photography model data.

[0128] As an option of the embodiment of this specification, the determining the longitude and latitude coordinates of the center point of the model corresponding to the bounding box range includes:

[0129] Determine the model center point corresponding to the bounding box range based on the center point positioning method, and determine the center point data address corresponding to the model center point;

[0130] Determine the longitude and latitude coordinates of the model center point corresponding to the center point data address.

[0131] As an optional embodiment of this specification, the method for determining the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method includes:

[0132] Determine the geographic coordinates corresponding to the longitude and latitude coordinates of the center point of the model based on the longitude and latitude format conversion;

[0133] A terrain database corresponding to the terrain elevation data is determined based on a terrain height acquisition method, and the terrain height of the model center point corresponding to the geographic coordinates is queried in the terrain database.

[0134] As an optional embodiment of this specification, the method of determining the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the coordinates of the combined center point based on the Cartesian coordinate conversion method includes:

[0135] Determine the original center point coordinates corresponding to the latitude and longitude coordinates of the center point of the model;

[0136] Determine coordinate parameters corresponding to the original center point coordinates and the combined center point coordinates respectively, wherein the coordinate parameters include longitude value, latitude value and altitude value;

[0137] Cartesian coordinate transformation is performed on each of the coordinate parameters to obtain a first Cartesian coordinate corresponding to the original center point coordinate and a second Cartesian coordinate corresponding to the combined center point coordinate.

[0138] As an option of the embodiment of this specification, the determining the translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate based on the three-dimensional space translation method includes:

[0139] Determine a coordinate difference between the first Cartesian coordinate and the second Cartesian coordinate based on the difference component, and determine a translation component corresponding to the coordinate difference;

[0140] The translation component is mapped into an initial four-dimensional matrix based on a three-dimensional space translation method to obtain a translation matrix.

[0141] As an optional embodiment of this specification, the step of converting and loading all the oblique photography model data based on the translation matrix to obtain a target conversion photography model includes:

[0142] Convert all the oblique photography model data with the translation matrix respectively to obtain terrain height conversion data;

[0143] All the terrain height conversion data are loaded and modeled to obtain a target photography model.

[0144] The embodiments of this specification also provide a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0145] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0146] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0147] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0148] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0149] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0150] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program codes.

[0151] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by entering a program to instruct related hardware, and the program may be stored in a computer-readable memory, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0152] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for optimizing loading of oblique photography model data, characterized in that: The method comprises: Obtain oblique photography model data and terrain elevation data, determine the bounding box range corresponding to the oblique photography model data based on the coordinate maximum method, and determine the longitude and latitude coordinates of the model center point corresponding to the bounding box range; Determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method; Integrate the latitude and longitude coordinates of the center point of the model and the terrain height of the center point of the model to obtain the coordinates of the combined center point, and determine the first Cartesian coordinates corresponding to the latitude and longitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the coordinates of the combined center point based on the Cartesian coordinate conversion method; The translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate is determined based on a three-dimensional space translation method, and all the oblique photography model data are converted and loaded based on the translation matrix to obtain a target conversion photography model.

2. The method according to claim 1, characterized in that: The determining the bounding box range corresponding to the oblique photography model data based on the coordinate extremum method includes: Determine at least two model tiles corresponding to the oblique photography model based on the oblique photography model data; The single tile range corresponding to each model tile is determined based on the coordinate extremum method, and all the single tile ranges are merged to obtain the bounding box range corresponding to the oblique photography model data.

3. The method according to claim 1, characterized in that Determining the latitude and longitude coordinates of the model center point corresponding to the bounding box range includes: Determine the model center point corresponding to the bounding box range based on the center point positioning method, and determine the center point data address corresponding to the model center point; Determine the longitude and latitude coordinates of the model center point corresponding to the center point data address.

4. The method according to claim 1, characterized in that: The method for determining the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on the terrain height acquisition method includes: Determine the geographic coordinates corresponding to the longitude and latitude coordinates of the center point of the model based on the longitude and latitude format conversion; A terrain database corresponding to the terrain elevation data is determined based on a terrain height acquisition method, and the terrain height of the model center point corresponding to the geographic coordinates is queried in the terrain database.

5. The method according to claim 1, characterized in that The method of respectively determining the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the coordinates of the combined center point based on the Cartesian coordinate conversion method includes: Determine the original center point coordinates corresponding to the latitude and longitude coordinates of the center point of the model; Determine coordinate parameters corresponding to the original center point coordinates and the combined center point coordinates respectively, wherein the coordinate parameters include longitude value, latitude value and altitude value; Cartesian coordinate transformation is performed on each of the coordinate parameters to obtain a first Cartesian coordinate corresponding to the original center point coordinate and a second Cartesian coordinate corresponding to the combined center point coordinate.

6. The method according to claim 1, characterized in that The determining of the translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate based on the three-dimensional space translation method includes: Determine a coordinate difference between the first Cartesian coordinate and the second Cartesian coordinate based on the difference component, and determine a translation component corresponding to the coordinate difference; The translation component is mapped into an initial four-dimensional matrix based on a three-dimensional space translation method to obtain a translation matrix.

7. The method according to claim 1, characterized in that The step of converting and loading all the oblique photography model data based on the translation matrix to obtain a target conversion photography model includes: Convert all the oblique photography model data with the translation matrix respectively to obtain terrain height conversion data; All the terrain height conversion data are loaded and modeled to obtain a target photography model.

8. An optimized loading device for oblique photography model data, characterized in that: The device comprises: An acquisition module, used to acquire oblique photography model data and terrain elevation data, determine the bounding box range corresponding to the oblique photography model data based on the coordinate maximum value method, and determine the longitude and latitude coordinates of the model center point corresponding to the bounding box range; A determination module, used to determine the terrain height of the model center point corresponding to the latitude and longitude coordinates of the model center point and the terrain elevation data based on a latitude and longitude format conversion method; An integration module is used to integrate the longitude and latitude coordinates of the center point of the model and the terrain height of the center point to obtain the combined coordinates of the center point of the model, and determine the Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the combined coordinates of the center point of the model based on the Cartesian coordinate conversion method to obtain the first Cartesian coordinates corresponding to the longitude and latitude coordinates of the center point of the model and the second Cartesian coordinates corresponding to the combined coordinates of the center point of the model; The loading module is used to determine the translation matrix corresponding to the first Cartesian coordinate and the second Cartesian coordinate based on the three-dimensional space translation method, and to convert and load all the oblique photography model data based on the translation matrix to obtain a target conversion photography model.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer-readable storage medium has instructions stored therein, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the method according to any one of claims 1 to 7.

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