CN113628331B - Data organization and scheduling method for photogrammetry model in illusion engine - Google Patents
Data organization and scheduling method for photogrammetry model in illusion engine Download PDFInfo
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Abstract
The application relates to a data organization and scheduling method, a device, a computer device and a storage medium of a photogrammetry model in a illusion engine. The method comprises the steps of reconstructing virtual nodes upwards according to a quadtree structure by deleting redundant data divided by a non-quadtree in a photogrammetry model tile tree to obtain a reconstructed quadtree; obtaining a tile tree in a visual field range in a reconstruction quadtree through viewing cone cutting, traversing nodes of the tile tree in the visual field range, obtaining the area of a grid model of a current node and the resolution of a corresponding texture picture, obtaining the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, requesting to load the current node when the current node error is not greater than the error of screen display, and performing data scheduling on Uasset format data of the node requesting to be loaded for visualization of a photogrammetry model in a illusion engine.
Description
Technical Field
The present disclosure relates to the field of digital twinning technology, and in particular, to a method, an apparatus, a computer device, and a storage medium for organizing and scheduling data of a photogrammetry model in a phantom engine.
Background
The digital twin city is a complex technology and application system (Gu Jianxiang et al, n.d.) for the new smart city, and the construction of the digital twin city has been raised to the national strategic level (Guo Renzhong et al, 2020). In the context of smart cities, digital twinning can build a visual high-fidelity three-dimensional scene for supporting testing and decision-making for a region
et al, 2018), it is therefore first necessary to construct a unified spatial "data backplane" with location information, to present the real geographic coordinates of the city in a virtual environment (Mao, 2014).
The oblique photogrammetry model is an indispensable data backplane for implementing digital twinning cities. Compared with a tile pyramid structure based on quadtree partitioning, the oblique photogrammetry model additionally performs model geometric thinning and texture rank reduction compression on root nodes at the upper layer part of the tile pyramid, the data organization mode in the prior art is not suitable for a game engine, and meanwhile, the traditional data scheduling method is not in line with the data organization mode after the game engine is improved.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a data organization and scheduling method, apparatus, computer device, and storage medium for a photogrammetry model in a phantom engine that can accommodate the phantom engine data.
A method of data organization and scheduling of photogrammetry models in a phantom engine, the method comprising:
acquiring OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree;
in the current frame, cutting a tile tree in a visual field range in the reconstructed quadtree through a view cone, traversing nodes of the tile tree in the visual field range, acquiring the area of the grid model of the current node and the resolution of the corresponding texture picture, acquiring the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not greater than the error of screen display;
the Uasset format data of the node requesting loading is data scheduled for visualization of the photogrammetry model in the illusion engine.
In one embodiment, the method further comprises: deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree; the virtual node is a non-data null node.
In one embodiment, the method further comprises: acquiring a visual vertebral body; constructing a bounding box for a tile tree in the reconstructed quadtree; and if the bounding box intersects the visual cone, judging that the tile tree corresponding to the bounding box is in the visual field range.
In one embodiment, the method further comprises: obtaining a current node error of the current node corresponding level according to the area of the grid model and the resolution of the texture picture, wherein the current node error is as follows:
wherein NGPE represents the current node error and a represents the area of the mesh model; b represents the resolution of the texture picture.
In one embodiment, the method further comprises: in the reconstructed quadtree, the deeper the layer number is, the smaller the current node error NGPE value is.
In one embodiment, the method further comprises: projecting the nodes to a near plane of a view cone, and calculating the approximate tile area per unit pixel in the display screen under the current viewpoint as follows:
wherein SGPE is the approximate tile area, D represents the distance between the view cone viewpoint and the node, FOV represents the field of view of the frustum, SR represents screen resolution, tan (-) represents tangent trigonometric function;
taking the approximate tile area as an error of screen display;
and requesting to load the current node when the error of the current node is not larger than the error of the screen display.
A data organization and scheduling apparatus for photogrammetry models in a phantom engine, the apparatus comprising:
the system comprises an OSGB data acquisition module, a virtual engine and a virtual engine, wherein the OSGB data acquisition module is used for acquiring OSGB data of the photogrammetry model and converting the OSGB data into Uasset format data in the virtual engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
the reconstruction quadtree construction module is used for deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards on the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstruction quadtree;
the data scheduling module is used for obtaining a tile tree in a visual field range in the reconstruction quadtree through view cone cutting in a current frame, traversing nodes of the tile tree in the visual field range, obtaining the area of the grid model of the current node and the resolution of the corresponding texture picture, obtaining a current node error of a corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not larger than the error displayed on a screen;
and the visualization module is used for carrying out data scheduling on Uasset format data of the node which requests loading and is used for visualizing the photogrammetry model in the illusion engine.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
acquiring OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree;
in the current frame, cutting a tile tree in a visual field range in the reconstructed quadtree through a view cone, traversing nodes of the tile tree in the visual field range, acquiring the area of the grid model of the current node and the resolution of the corresponding texture picture, acquiring the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not greater than the error of screen display;
the Uasset format data of the node requesting loading is data scheduled for visualization of the photogrammetry model in the illusion engine.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree;
in the current frame, cutting a tile tree in a visual field range in the reconstructed quadtree through a view cone, traversing nodes of the tile tree in the visual field range, acquiring the area of the grid model of the current node and the resolution of the corresponding texture picture, acquiring the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not greater than the error of screen display;
the Uasset format data of the node requesting loading is data scheduled for visualization of the photogrammetry model in the illusion engine.
The data organization and scheduling method, the device, the computer equipment and the storage medium of the photogrammetry model in the illusion engine are used for converting the OSGB data into Uasset format data in the illusion engine by acquiring the OSGB data of the photogrammetry model; deleting redundant data divided by a non-quadtree in the photogrammetry model tile tree, and upwards reconstructing virtual nodes according to the quadtree structure to obtain a reconstructed quadtree; obtaining a tile tree in a visual field range in a reconstruction quadtree through viewing cone cutting, traversing nodes of the tile tree in the visual field range, obtaining the area of a grid model of a current node and the resolution of a corresponding texture picture, obtaining the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not greater than the error displayed by a screen; the Uasset format data of the node requesting loading is data scheduled for visualization of the photogrammetry model in the illusion engine. The invention provides a data reorganization method of an oblique photography model based on a full-rank quadtree, and the grid sparseness of tiles is related with the corresponding texture size to be used as a judgment standard of the fine degree of the tiles, so that the loading data is simplified, the efficiency is improved, and the data scheduling independent of the data hierarchy relation is realized.
Drawings
FIG. 1 is a flow diagram of a method for organizing and scheduling data for a photogrammetry model in a phantom engine, according to one embodiment;
FIG. 2 is a schematic diagram of a tile pyramid model of a tilted photogrammetry model in one embodiment;
FIG. 3 is a schematic diagram of a tile pyramid with redundant data deleted in one embodiment;
FIG. 4 is a schematic diagram of a reconstructed quadtree with virtual nodes at the upper layer and real nodes at the lower layer in one embodiment;
FIG. 5 is a schematic view of a cone cutting principle in one embodiment;
FIG. 6 is a schematic diagram illustrating a computing principle of an SGPE in one embodiment;
FIG. 7 is a schematic diagram of data composition of a tilted photogrammetry tile in one embodiment;
FIG. 8 is a graph of index efficiency versus result from higher field of view to lower field of view under a fixed camera path in one embodiment;
FIG. 9 is a block diagram of a visualization device of a photogrammetry model in a phantom engine in one embodiment;
fig. 10 is an internal structural view of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The data organization and scheduling method of the photogrammetry model in the illusion engine can be applied to the following application environments. The terminal executes a data organization and scheduling method of a photogrammetry model in the illusion engine, and converts OSGB data into Uasset format data in the illusion engine by acquiring the OSGB data of the photogrammetry model; and deleting redundant data divided by a non-quadtree in the photogrammetry model tile tree, upwards reconstructing virtual nodes according to a quadtree structure to obtain a reconstructed quadtree, and using the grid sparseness degree of the tile and the corresponding texture size as a judgment standard of the tile fineness degree to realize data scheduling independent of the existing hierarchical relation of data production. The terminal may be, but not limited to, various personal computers, notebook computers, and tablet computers.
In one embodiment, as shown in fig. 1, a method for organizing and scheduling data of a photogrammetry model in a phantom engine is provided, comprising the steps of:
The oblique photogrammetry model is one of the most important basic data for constructing a digital twin city scene, and a three-dimensional scene dataset at the city level may consist of hundreds of millions of triangles. Compared with the tile pyramid structure based on quadtree partitioning, the oblique photogrammetry model additionally performs model geometric thinning and texture rank reduction compression on the root node at the upper layer part of the tile pyramid, as shown in fig. 2, and the number of non-quadtree partitioning layers is not equal for different tile trees due to different original data amounts of each block area, and the lower layer part of the tile pyramid is partitioned according to the quadtree structure.
The domestic oblique photography data are mostly stored in an OSGB data format, wherein the OSGB data format is defined by a three-dimensional engine, and the binary storage is used for accelerating computer reading. The OSGB data includes a mesh model and a corresponding texture picture.
And 104, deleting redundant data divided by a non-quadtree in the tile tree, and upwards reconstructing virtual nodes of the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree.
The invention provides a reorganization method which comprises the following steps:
(1) The non-quadtree partitioning hierarchy is deleted such that the tile trees conform to the quadtree data structure partitioning, as shown in fig. 3. However, since the different tile tree non-quadtree division levels depend on the data size of the corresponding region, the depths of the different tile trees are not consistent after deletion;
(2) The virtual nodes are further reconstructed upwards according to the quadtree structure (nodes of the quadtree are constructed upwards according to the geographical scope, but no real data only serve as an index function), and finally a quadtree with the virtual nodes at the upper layer and the real nodes at the lower layer is synthesized, as shown in fig. 4. Wherein the hierarchy is independent of the tile fineness and therefore cannot employ a scheduling method related to the number of hierarchies.
And 106, in the current frame, obtaining a tile tree in the visual field range in the reconstructed quadtree through viewing cone cutting, traversing nodes of the tile tree in the visual field range, obtaining the area of a grid model of the current node and the resolution of a corresponding texture picture, obtaining the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not larger than the error of screen display.
The visual space of the human eye as a perspective projection viewpoint is a cone, which is used to simulate such visual space. Because the data volume of the oblique photography model is relatively large and the hierarchical relationship of the corresponding tile data is complex, the data cannot be fully loaded into the memory at one time. When a user browses data, only the tiles in the view cone range are observed, the corresponding detail level of the tiles to be loaded is determined according to a scene scheduling principle, and after the CPU calculates the tiles to be loaded, the triangles to be drawn are sent to the GPU, so that the data scheduling efficiency can be greatly improved through the process.
For example, in FIG. 5, we have created a bounding box for each object in the scene. If the bounding box does not intersect the view cone, we do not need to add the object to the load queue. Thus, view cone clipping can greatly reduce the processing pressure of the client in the post scene rendering.
In the data organization and scheduling method of the photogrammetry model in the illusion engine, redundant data divided by non-quadtree in the photogrammetry model tile tree is deleted, and virtual nodes are reconstructed upwards according to the quadtree structure, so that a reconstructed quadtree is obtained; obtaining a tile tree in a visual field range in a reconstruction quadtree through viewing cone cutting, traversing nodes of the tile tree in the visual field range, obtaining the area of a grid model of a current node and the resolution of a corresponding texture picture, obtaining the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, requesting to load the current node when the current node error is not greater than the error of screen display, and performing data scheduling on Uasset format data of the node requesting to be loaded for visualization of a photogrammetry model in a illusion engine. The invention provides a data reorganization method of an oblique photography model based on a full-rank quadtree, and the grid sparseness of tiles is related with the corresponding texture size to be used as a judgment standard of the fine degree of the tiles, so that the loading data is simplified, the efficiency is improved, and the data scheduling independent of the data hierarchy relation is realized.
In one embodiment, the method further comprises: deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree; the virtual nodes are non-data null nodes.
The virtual nodes have no real data and only serve as an index.
In one embodiment, the method further comprises: acquiring a visual vertebral body; constructing a bounding box for a tile tree in the reconstructed quadtree; if the bounding box intersects with the cone, judging that the tile tree corresponding to the bounding box is in the visual field range.
In one embodiment, the method further comprises: the current node error of the corresponding level of the current node is obtained according to the area of the grid model and the resolution ratio of the texture picture, and is as follows:
wherein, NGPE represents the current node error, a represents the area of the grid model; b represents the resolution of the texture picture.
Because a unified pyramid with inconsistent hierarchical precision is used at the same tree level, the parameters defined by the tile scope in the prior art cannot accurately describe the precision of the tile. However, tiles consist of a grid and texture, which can be used to interpret tile accuracy. As the number of layers increases, the surface area of the tile is smaller and smaller, the number of pixels in the texture is similar between adjacent levels, and the trend of increasing between multiple levels is shown. Thus, the formula
The NGPE in (a) represents the geometric grid area of a unit pixel in each node level and can be used to distinguish nodes of different grid areas at different levels. />
In one embodiment, the method further comprises: in the reconstructed quadtree, the deeper the layer number, the smaller the current node error NGPE value.
In one embodiment, the method further comprises: projecting the nodes to the near plane of the view cone, and calculating the approximate tile area of each unit pixel in the display screen under the current viewpoint as follows:
the calculation principle of SGPE is shown in fig. 6, where SGPE is an approximate tile area, D represents the distance between the view cone viewpoint and the node, FOV represents the field of view of the frustum, SR represents the screen resolution, and Tan (·) represents the tangent trigonometric function;
taking the approximate tile area as the error of screen display; when the error of the current node is not larger than the error of the screen display, requesting to load the current node, namely when the NGPE is larger than the SGPE, the error of the corresponding level of the node is larger than the error of the screen display, and continuing traversing. Otherwise, the current node is loaded. In this way, uniform standard loading between multi-region tile trees can be achieved for oblique photogrammetry models under different production standards. In addition, they can be reorganized into scene trees for load scheduling, which has important significance for fusing multi-source data and establishing uniform spatial references. For example, FIG. 7 illustrates data for 18-layer tiles and 20-layer tiles. The deeper the layer number, the smaller the data NGPE value, and the appropriate level is selected along the quadtree traversal nodes.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
In a specific embodiment, a set of control experiments is set for the unified quadtree method, and the experiment environment CPU adopted in the experiment is: inter (R) Core (TM) i7-9750H CPU@2.60GHZ. Comparing the index efficiency under the scene traversal of the block-based quadtree and the reconstructed virtual node quadtree, the fixed path from higher visual field height to lower visual field height is set as the camera track, the loading tiles have more coarse levels to less fine levels of the tile number, and the comparison result is shown in fig. 8, so that the index efficiency of the reconstructed virtual node is higher along with the finer loading levels, and the method is suitable for being used as an index scheme in a large-scale HLOD oblique photography model.
In one embodiment, as shown in fig. 9, there is provided a data organization and scheduling apparatus of a photogrammetry model in a illusion engine, comprising: OSGB data acquisition module 902, reconstruction quadtree construction module 904, data scheduling module 906, and visualization module 908, wherein:
the OSGB data obtaining module 902 is configured to obtain OSGB data of the photogrammetry model, and convert the OSGB data into data in the uoset format in the illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
a reconstruction quadtree construction module 904, configured to delete redundant data divided by non-quadtree in the tile tree, and reconstruct virtual nodes upwards for the tile tree deleted with the redundant data according to the quadtree structure, to obtain a reconstruction quadtree;
the data scheduling module 906 is configured to obtain, in the current frame, a tile tree in the view field range in the reconstructed quadtree by means of view cone clipping, traverse nodes of the tile tree in the view field range, obtain an area of a grid model of the current node and a resolution of a corresponding texture picture, obtain a current node error of a corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and request loading of the current node when the current node error is not greater than an error displayed on a screen;
the visualization module 908 is configured to schedule data in the uaset format of the node that requests loading, and is used for visualizing the photogrammetry model in the illusion engine.
The reconstruction quadtree construction module 904 is further configured to delete redundant data divided by non-quadtree in the tile tree, and reconstruct virtual nodes upwards on the tile tree deleted with the redundant data according to the quadtree structure to obtain a reconstruction quadtree; the virtual nodes are non-data null nodes.
The data scheduling module 906 is further configured to obtain an optic cone; constructing a bounding box for a tile tree in the reconstructed quadtree; if the bounding box intersects with the cone, judging that the tile tree corresponding to the bounding box is in the visual field range.
The data scheduling module 906 is further configured to obtain, according to the area of the mesh model and the resolution of the texture picture, a current node error of a current node corresponding level as follows:
wherein, NGPE represents the current node error, a represents the area of the grid model; b represents the resolution of the texture picture.
The data scheduling module 906 is further configured to project the node to a near plane of the view cone, and calculate an approximate tile area per unit pixel in the display screen at the current viewpoint as:
wherein SGPE is an approximate tile area, D represents the distance between the view point of the view cone and the node, FOV represents the field of view of the frustum, SR represents the screen resolution, and Tan (&) represents the tangent trigonometric function;
taking the approximate tile area as the error of screen display; and when the error of the current node is not larger than the error of the screen display, requesting to load the current node.
For specific limitations on the data organization and scheduling means of the photogrammetry model in the illusion engine, reference is made to the above limitation on the data organization and scheduling method of the photogrammetry model in the illusion engine, and no further description is given here. The various modules in the data organization and scheduling means of the photogrammetry model in the illusion engine described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and an internal structure diagram thereof may be as shown in fig. 10. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method for organizing and scheduling data for a photogrammetry model in a phantom engine. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 10 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In an embodiment a computer device is provided comprising a memory storing a computer program and a processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A method for organizing and scheduling data of photogrammetry models in a phantom engine, the method comprising:
acquiring OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree;
in the current frame, cutting a tile tree in a visual field range in the reconstructed quadtree through a view cone, traversing nodes of the tile tree in the visual field range, acquiring the area of the grid model of the current node and the resolution of the corresponding texture picture, acquiring the current node error of the corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not greater than the error of screen display;
the Uasset format data of the node requesting loading is data scheduled for visualization of the photogrammetry model in the illusion engine.
2. The method of claim 1, wherein deleting redundant data of non-quadtree partitions in the tile tree, reconstructing virtual nodes upward from the tile tree from which the redundant data was deleted according to a quadtree structure, to obtain a reconstructed quadtree, comprising:
deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstructed quadtree; the virtual node is a non-data null node.
3. The method of claim 2, wherein obtaining a tile tree in the reconstructed quadtree in view by view cone cropping comprises:
acquiring a visual vertebral body;
constructing a bounding box for a tile tree in the reconstructed quadtree;
and if the bounding box intersects the visual cone, judging that the tile tree corresponding to the bounding box is in the visual field range.
4. A method according to claim 3, wherein deriving the current node error for the current node corresponding level from the area of the mesh model and the resolution of the texture picture comprises:
obtaining a current node error of the current node corresponding level according to the area of the grid model and the resolution of the texture picture, wherein the current node error is as follows:
wherein NGPE represents the current node error and a represents the area of the mesh model; b represents the resolution of the texture picture.
5. The method of claim 4, wherein the deeper the number of layers in the reconstructed quadtree, the smaller the current node error NGPE value.
6. The method of claim 5, wherein requesting loading the current node when the current node error is not greater than an error of a screen display comprises:
projecting the nodes to a near plane of a view cone, and calculating the approximate tile area per unit pixel in the display screen under the current viewpoint as follows:
wherein SGPE is the approximate tile area, D represents the distance between the view cone viewpoint and the node, FOV represents the field of view of the frustum, SR represents screen resolution, tan (-) represents tangent trigonometric function;
taking the approximate tile area as an error of screen display;
and requesting to load the current node when the error of the current node is not larger than the error of the screen display.
7. A data organization and scheduling apparatus for photogrammetry models in a phantom engine, the apparatus comprising:
the system comprises an OSGB data acquisition module, a virtual engine and a virtual engine, wherein the OSGB data acquisition module is used for acquiring OSGB data of the photogrammetry model and converting the OSGB data into Uasset format data in the virtual engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetry model comprises a plurality of tile trees;
the reconstruction quadtree construction module is used for deleting redundant data divided by non-quadtree in the tile tree, and reconstructing virtual nodes upwards on the tile tree with the redundant data deleted according to the quadtree structure to obtain a reconstruction quadtree;
the data scheduling module is used for obtaining a tile tree in a visual field range in the reconstruction quadtree through view cone cutting in a current frame, traversing nodes of the tile tree in the visual field range, obtaining the area of the grid model of the current node and the resolution of the corresponding texture picture, obtaining a current node error of a corresponding level of the current node according to the area of the grid model and the resolution of the texture picture, and requesting to load the current node when the current node error is not larger than the error displayed on a screen;
and the visualization module is used for carrying out data scheduling on Uasset format data of the node which requests loading and is used for visualizing the photogrammetry model in the illusion engine.
8. The apparatus of claim 7, wherein the data scheduling module is further configured to obtain, from the area of the mesh model and the resolution of the texture picture, a current node error at the current node corresponding level as:
wherein NGPE represents the current node error and a represents the area of the mesh model; b represents the resolution of the texture picture.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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