CN113628331A - Data organization and scheduling method of photogrammetry model in illusion engine - Google Patents
Data organization and scheduling method of photogrammetry model in illusion engine Download PDFInfo
- Publication number
- CN113628331A CN113628331A CN202111008307.2A CN202111008307A CN113628331A CN 113628331 A CN113628331 A CN 113628331A CN 202111008307 A CN202111008307 A CN 202111008307A CN 113628331 A CN113628331 A CN 113628331A
- Authority
- CN
- China
- Prior art keywords
- data
- current node
- quadtree
- tile
- model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/005—Tree description, e.g. octree, quadtree
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
- G06T17/205—Re-meshing
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Processing Or Creating Images (AREA)
Abstract
The application relates to a data organization and scheduling method and device of a photographic measurement model in a ghost engine, computer equipment and a storage medium. Deleting redundant data divided by non-quadtrees in a photogrammetric model tile tree, and upwards reconstructing virtual nodes according to a quadtree structure to obtain a reconstructed quadtree; the method comprises the steps of obtaining a tile tree in a reconstructed quadtree within a visual field range through frustum cutting, traversing nodes of the tile tree within 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 current node at the corresponding level 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 larger than the error displayed on a screen, and performing data scheduling on Uasset format data of the node requesting to be loaded for visualization of a photographic measurement model in a phantom engine.
Description
Technical Field
The application relates to the technical field of digital twinning, in particular to a data organization and scheduling method and device of a photographic measurement model in a ghost engine, computer equipment and a storage medium.
Background
The digital twin city is a set of complex technology and application system (consider auspicious et al, n.d.) for a novel smart city, and the construction of the digital twin city is raised to the national strategic level (Guo ren faith et al, 2020). In the context of smart cities, digital twins can create a visual high-fidelity three-dimensional scene for supporting tests and decisions for a region (et al, 2018), therefore, it is first necessary to construct a unified spatial "data backplane" with location information, presenting 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 twin cities. Compared with a tile pyramid structure based on quadtree division, the oblique photogrammetry model can additionally perform model geometric thinning and texture rank reduction compression on the root node 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 accordance with the improved data organization mode of the game engine.
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 photogrammetric model in a ghost engine that can adapt to ghost engine data.
A method of data organization and scheduling of photogrammetry models in a ghost engine, the method comprising:
obtaining OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a ghost engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetric model comprises a plurality of tile trees;
deleting redundant data which are not divided by the 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 a current frame, a tile tree in a visual field range in the reconstructed quadtree is obtained through frustum cutting, nodes of the tile tree in the visual field range are traversed, the area of the grid model of the current node and the resolution of the texture picture corresponding to the area are obtained, a current node error of the current node corresponding to the level is obtained according to the area of the grid model and the resolution of the texture picture, and when the current node error is not larger than the error displayed on a screen, the current node is requested to be loaded;
and performing data scheduling on the Uasset format data of the nodes requested to be loaded for visualizing the photographic measurement model in the illusion engine.
In one embodiment, the method further comprises the following steps: deleting redundant data which are not divided by the 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 data-free empty nodes.
In one embodiment, the method further comprises the following steps: acquiring a visual vertebral body; constructing bounding boxes for tile trees in the reconstructed quadtree; and if the bounding box is intersected with the view cone, judging that the tile tree corresponding to the bounding box is in the view field range.
In one embodiment, the method further comprises the following steps: obtaining the current node error of the current node corresponding level according to the area of the grid model and the resolution of the texture picture as follows:
wherein NGPE represents the current node error, a represents the area of the mesh model; b represents the resolution of the texture picture.
In one embodiment, the method further comprises the following steps: and in the reconstructed quadtree, the deeper the layer number is, the smaller the error NGPE value of the current node is.
In one embodiment, the method further comprises the following steps: projecting the node to a near plane of a viewing cone, and calculating the area of an approximate tile of each unit pixel in a display screen under the current viewpoint as follows:
wherein SGPE is the approximate tile area, D represents the distance between the view point of the viewing cone and the node, FOV represents the view point of the frustum, SR represents the screen resolution, and Tan (·) represents a 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 displayed on the screen, requesting to load the current node.
An apparatus for organizing and scheduling data for a photogrammetry model in a ghost engine, the apparatus comprising:
the OSGB data acquisition module is used for acquiring OSGB data of a photogrammetric model and converting the OSGB data into Uasset format data in an illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetric model comprises a plurality of tile trees;
the reconstruction quadtree construction module is used for deleting redundant data which are not divided by the quadtree in the tile tree and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to a quadtree structure to obtain a reconstruction quadtree;
the data scheduling module is used for obtaining a tile tree in the reconstruction quadtree within a visual field range by frustum cutting in a current frame, traversing nodes of the tile tree within the visual field range, obtaining the area of the grid model of the current node and the resolution of the texture picture corresponding to the area of the grid model, obtaining the current node error of the current node at the corresponding level 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 on a screen;
and the visualization module is used for carrying out data scheduling on the Uasset format data of the nodes requested to be loaded and visualizing the photographic measurement model in the illusion engine.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
obtaining OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a ghost engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetric model comprises a plurality of tile trees;
deleting redundant data which are not divided by the 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 a current frame, a tile tree in a visual field range in the reconstructed quadtree is obtained through frustum cutting, nodes of the tile tree in the visual field range are traversed, the area of the grid model of the current node and the resolution of the texture picture corresponding to the area are obtained, a current node error of the current node corresponding to the level is obtained according to the area of the grid model and the resolution of the texture picture, and when the current node error is not larger than the error displayed on a screen, the current node is requested to be loaded;
and performing data scheduling on the Uasset format data of the nodes requested to be loaded for visualizing the photographic measurement model in the illusion engine.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
obtaining OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a ghost engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetric model comprises a plurality of tile trees;
deleting redundant data which are not divided by the 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 a current frame, a tile tree in a visual field range in the reconstructed quadtree is obtained through frustum cutting, nodes of the tile tree in the visual field range are traversed, the area of the grid model of the current node and the resolution of the texture picture corresponding to the area are obtained, a current node error of the current node corresponding to the level is obtained according to the area of the grid model and the resolution of the texture picture, and when the current node error is not larger than the error displayed on a screen, the current node is requested to be loaded;
and performing data scheduling on the Uasset format data of the nodes requested to be loaded for visualizing the photographic measurement model in the illusion engine.
The data organization and scheduling method, device, computer equipment and storage medium of the photogrammetry model in the ghost engine convert OSGB data into Uasset format data in the ghost engine by acquiring OSGB data of the photogrammetry model; deleting redundant data divided by non-quadtrees in the photogrammetric model tile tree, and upwards reconstructing virtual nodes according to a quadtree structure to obtain a reconstructed quadtree; obtaining a tile tree in a reconstruction quadtree within a visual field range through frustum cutting, traversing nodes of the tile tree within 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 current node at the corresponding level 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 on a screen; and performing data scheduling on the Uasset format data of the nodes requested to be loaded for visualizing the photographic measurement model in the illusion engine. The invention provides a data reorganization method of a full-rank quadtree-based oblique photography model, and relates the grid sparsity degree of a tile and the size of the corresponding texture as a judgment standard of the tile fineness degree, so that the data loading 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 illustrating a method for organizing and scheduling data for a photogrammetric model in a ghost engine, according to one embodiment;
FIG. 2 is a schematic view of a tile pyramid model of an oblique 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 diagram illustrating a reconstructed quadtree with virtual nodes at the top and real nodes at the bottom according to an embodiment;
FIG. 5 is a schematic view of the viewing frustum cutting principle in one embodiment;
FIG. 6 is a schematic diagram illustrating the calculation of an SGPE according to one embodiment;
FIG. 7 is a schematic diagram of the data composition of oblique photogrammetry tiles in one embodiment;
FIG. 8 is a graph illustrating the comparison of index efficiency from a higher field of view height to a lower field of view height for a fixed camera path in one embodiment;
FIG. 9 is a block diagram of an embodiment of an apparatus for visualizing a photogrammetric model in a ghost engine;
FIG. 10 is a diagram showing an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application 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 ghost engine, and the OSGB data are converted into Uasset format data in the ghost engine by acquiring the OSGB data of the photogrammetry model; and deleting redundant data divided by non-quadtrees in the photogrammetric model tile tree, reconstructing virtual nodes upwards according to the quadtree structure to obtain a reconstructed quadtree, and associating the grid sparsity of the tiles with the corresponding texture size to serve as a judgment standard of the tile fineness, so that data scheduling independent of the existing hierarchical relation of data production is realized. The terminal may be, but is not limited to, various personal computers, notebook computers, and tablet computers.
In one embodiment, as shown in fig. 1, there is provided a data organization and scheduling method for photogrammetry models in a ghost engine, comprising the steps of:
The oblique photogrammetry model is one of the most important basic data for constructing digital twin urban scenes, and a three-dimensional scene data set at the urban level may consist of hundreds of millions of triangles. Compared with a tile pyramid structure based on quad-tree division, the oblique photogrammetry model additionally performs model geometric thinning and texture rank reduction compression on root nodes in the upper layer part of the tile pyramid, as shown in fig. 2, and because the original data volume of each block of area is different, the number of non-quad-tree division layers is not equal for different tile trees, and the lower layer part of the tile pyramid is divided according to the quad-tree structure.
Domestic oblique photography data are mostly stored in an OSGB data format, the OSGB data format is a data format defined by a three-dimensional engine, and binary storage is used, so that computer reading can be accelerated. The OSGB data includes a mesh model and a corresponding texture picture.
And 104, deleting redundant data which are not divided by the 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 removed to make the tile tree conform to the quadtree data structure partitioning, as shown in fig. 3. However, since the non-quadtree partitioning levels of different tile trees depend on the data size of the corresponding region, the depths of different tile trees are not consistent after deletion;
(2) the virtual nodes are continuously reconstructed upwards for all tile trees according to the quadtree structure (the nodes of the quadtree are constructed upwards according to the geographical range, but no real data is used for only serving as an index), 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. Where the level is independent of the tile granularity, scheduling methods related to the number of levels cannot be employed.
And 106, in the current frame, obtaining a tile tree in the reconstructed quadtree within the visual field range through frustum cutting, traversing nodes of the tile tree within 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 greater than the error displayed on a screen.
The visual space of the human eye as a perspective projection viewpoint is a cone, which is used to simulate such a visual space. Because the quantity of the oblique photography model data is large, and the hierarchical relation of the corresponding tile data is complex, the oblique photography model data cannot be loaded into the memory all at once. When a user browses data, only the tiles in the view cone range are observed, the corresponding detail levels of the tiles needing to be loaded are determined according to a scene scheduling principle, and after the tiles needing to be loaded are calculated by the CPU, the triangles needing to be drawn are sent to the GPU.
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 frustum, we do not need to add the object to the load queue. Therefore, the frustum cropping shear can greatly reduce the processing pressure of the client in the post scene rendering.
And step 108, performing data scheduling on the Uasset format data of the node requesting to be loaded, and using the Uasset format data for visualization of a photographic measurement model in the illusion engine.
In the data organization and scheduling method of the photogrammetry model in the illusion engine, a reconstructed quadtree is obtained by deleting redundant data which is not divided by the quadtree in a tile tree of the photogrammetry model and reconstructing virtual nodes upwards according to the quadtree structure; the method comprises the steps of obtaining a tile tree in a reconstructed quadtree within a visual field range through frustum cutting, traversing nodes of the tile tree within 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 current node at the corresponding level 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 larger than the error displayed on a screen, and performing data scheduling on Uasset format data of the node requesting to be loaded for visualization of a photographic measurement model in a phantom engine. The invention provides a data reorganization method of a full-rank quadtree-based oblique photography model, and relates the grid sparsity degree of a tile and the size of the corresponding texture as a judgment standard of the tile fineness degree, so that the data loading 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 the following steps: deleting redundant data which are not divided by the quadtree in the tile tree, and reconstructing virtual nodes upwards for the tile tree with the deleted redundant data according to the quadtree structure to obtain a reconstructed quadtree; the virtual nodes are data-free null nodes.
The virtual nodes have no real data and only serve as indexes.
In one embodiment, the method further comprises the following steps: acquiring a visual vertebral body; constructing a bounding box for the tile tree in the reconstructed quadtree; if the bounding box is intersected with the view centrum, the tile tree corresponding to the bounding box is judged to be in the view field.
In one embodiment, the method further comprises the following steps: 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 as follows:
the NGPE represents the current node error, and a represents the area of the grid model; b denotes the resolution of the texture picture.
Because a unified pyramid with inconsistent hierarchical precision is used at the same tree level, parameters defined only by tile ranges in the prior art cannot accurately describe the precision of tiles. However, tiles are composed of meshes and textures, which can be used to interpret tile precision. As the number of layers is increased, the surface area corresponding to the tile is smaller, the number of pixels in the texture is similar between adjacent levels, and the tiles show an increasing trend among multiple levels. Thus, the formulaThe NGPE in (1) represents the geometric grid area of a unit pixel in each node level, and can be used for distinguishing different nodesNodes of different grid areas of the levels.
In one embodiment, the method further comprises the following steps: in the reconstruction of the quadtree, the deeper the layer number is, the smaller the current node error NGPE value is.
In one embodiment, the method further comprises the following steps: projecting the nodes to the near plane of the view frustum, and calculating the area of an approximate tile of each unit pixel in the display screen under the current viewpoint as follows:
the calculation principle of the SGPE is shown in fig. 6, where SGPE is an approximate tile area, D represents the distance between the view point of the viewing pyramid and the node, FOV represents the view point of the frustum, SR represents the screen resolution, and Tan (·) represents a tangent trigonometric function;
taking the area of the approximate tile as the error of screen display; and when the error of the current node is not greater than the error of the screen display, requesting to load the current node, namely when the NGPE is greater than the SGPE, continuously traversing when the error of the corresponding level of the node is greater than the error of the screen display. Otherwise, loading the current node. In this way, unified standard loading between multi-region tile trees can be achieved for oblique photogrammetry models under different production standards. In addition, they can be recombined into a scene tree for loading scheduling, which is of great significance for fusing multi-source data and establishing a uniform spatial reference. For example, FIG. 7 illustrates data for an 18-layer tile and a 20-layer tile. The deeper the number of levels of the data NGPE, the smaller the value, the appropriate level is selected along the quadtree traversal node.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In a specific embodiment, a group of control experiments are set for the unified quadtree method, and the experiment environment CPU adopted in the experiment: inter (R) core (TM) i7-9750H CPU @2.60 GHZ. The indexing efficiency of the block-based quadtree and the reconstructed virtual node quadtree under scene traversal is compared, a fixed path from a higher view height to a lower view height is set as a camera track, the loaded tiles have more rough levels to a fewer fine levels, and the comparison result is shown in fig. 8.
In one embodiment, as shown in fig. 9, there is provided a data organization and scheduling apparatus for photogrammetry models in a ghost engine, comprising: an OSGB data acquisition module 902, a reconstructed quadtree construction module 904, a data scheduling module 906, and a visualization module 908, wherein:
an OSGB data obtaining module 902, configured to obtain OSGB data of the photogrammetric model, and convert the OSGB data into uaset format data 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 reconstructed quadtree construction module 904, configured to delete redundant data that is not partitioned by the quadtree in the tile tree, and reconstruct a virtual node upwards for the tile tree from which the redundant data is deleted according to the quadtree structure, so as to obtain a reconstructed quadtree;
a data scheduling module 906, configured to obtain, in a current frame, a tile tree in a view field range in the reconstructed quadtree through view frustum cutting, traverse nodes of the tile tree in the view field range, obtain an area of a mesh model of a current node and a resolution of a corresponding texture picture, obtain a current node error of a level corresponding to the current node according to the area of the mesh 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 of screen display;
and a visualization module 908, configured to perform data scheduling on the uaset format data of the node requesting to be loaded, for visualization of the photographic measurement model in the illusion engine.
The reconstructed quadtree construction module 904 is further configured to delete redundant data that is not partitioned by the quadtree in the tile tree, and reconstruct a virtual node upwards for the tile tree from which the redundant data is deleted according to the quadtree structure to obtain a reconstructed quadtree; the virtual nodes are data-free null nodes.
The data scheduling module 906 is further configured to obtain a visual cone; constructing a bounding box for the tile tree in the reconstructed quadtree; if the bounding box is intersected with the view centrum, the tile tree corresponding to the bounding box is judged to be in the view field.
The data scheduling module 906 is further configured to obtain a current node error at a current node corresponding level according to the area of the mesh model and the resolution of the texture picture as:
the NGPE represents the current node error, and a represents the area of the grid model; b denotes the resolution of the texture picture.
The data scheduling module 906 is further configured to project the nodes to a near plane of the view frustum, and calculate an approximate tile area per unit pixel in the display screen at the current viewpoint as:
wherein, SGPE is approximate tile area, D represents the distance between the view point of the viewing cone and the node, FOV represents the view point of the frustum, SR represents screen resolution, and Tan (·) represents tangent trigonometric function;
taking the area of the approximate tile as the error of screen display; and when the error of the current node is not larger than the error displayed on the screen, requesting to load the current node.
For specific limitations of the data organization and scheduling apparatus of the phantom engine camera measurement model, reference may be made to the above limitations on the data organization and scheduling method of the phantom engine camera measurement model, which are not described herein again. The various modules of the data organization and scheduling apparatus 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 modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram 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 comprises a nonvolatile 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 an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of data organization and scheduling of photogrammetric models in a ghost 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, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those 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 above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile 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), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for organizing and scheduling data for a photogrammetry model in a ghost engine, the method comprising:
obtaining OSGB data of a photogrammetry model, and converting the OSGB data into Uasset format data in a ghost engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetric model comprises a plurality of tile trees;
deleting redundant data which are not divided by the 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 a current frame, a tile tree in a visual field range in the reconstructed quadtree is obtained through frustum cutting, nodes of the tile tree in the visual field range are traversed, the area of the grid model of the current node and the resolution of the texture picture corresponding to the area are obtained, a current node error of the current node corresponding to the level is obtained according to the area of the grid model and the resolution of the texture picture, and when the current node error is not larger than the error displayed on a screen, the current node is requested to be loaded;
and performing data scheduling on the Uasset format data of the nodes requested to be loaded for visualizing the photographic measurement model in the illusion engine.
2. The method of claim 1, wherein removing redundant data from the tile tree that is not quadtree partitioned, and reconstructing virtual nodes up the tile tree with redundant data removed in a quadtree structure to obtain a reconstructed quadtree, comprises:
deleting redundant data which are not divided by the 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 data-free empty nodes.
3. The method of claim 2, wherein obtaining the tile tree in the reconstructed quadtree within the field of view by frustum cropping comprises:
acquiring a visual vertebral body;
constructing bounding boxes for tile trees in the reconstructed quadtree;
and if the bounding box is intersected with the view cone, judging that the tile tree corresponding to the bounding box is in the view field range.
4. The method of claim 3, wherein obtaining the current node error at the current node corresponding level according to the area of the mesh model and the resolution of the texture picture comprises:
obtaining the current node error of the current node corresponding level according to the area of the grid model and the resolution of the texture picture as follows:
wherein NGPE represents the current node error, a represents the area of the mesh model; b represents the resolution of the texture picture.
5. The method of claim 4, wherein the current node error NGPE value is smaller for a deeper level in the reconstructed quadtree.
6. The method of claim 5, wherein requesting loading of the current node when the current node error is not greater than the error of the screen display comprises:
projecting the node to a near plane of a viewing cone, and calculating the area of an approximate tile of each unit pixel in a display screen under the current viewpoint as follows:
wherein SGPE is the approximate tile area, D represents the distance between the view point of the viewing cone and the node, FOV represents the view point of the frustum, SR represents the screen resolution, and Tan (·) represents a 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 displayed on the screen, requesting to load the current node.
7. An apparatus for organizing and scheduling data for a photogrammetric model in a ghost engine, the apparatus comprising:
the OSGB data acquisition module is used for acquiring OSGB data of a photogrammetric model and converting the OSGB data into Uasset format data in an illusion engine; the OSGB data comprises a grid model and a corresponding texture picture; the photogrammetric model comprises a plurality of tile trees;
the reconstruction quadtree construction module is used for deleting redundant data which are not divided by the quadtree in the tile tree and reconstructing virtual nodes upwards for the tile tree with the redundant data deleted according to a quadtree structure to obtain a reconstruction quadtree;
the data scheduling module is used for obtaining a tile tree in the reconstruction quadtree within a visual field range by frustum cutting in a current frame, traversing nodes of the tile tree within the visual field range, obtaining the area of the grid model of the current node and the resolution of the texture picture corresponding to the area of the grid model, obtaining the current node error of the current node at the corresponding level 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 on a screen;
and the visualization module is used for carrying out data scheduling on the Uasset format data of the nodes requested to be loaded and visualizing the photographic measurement model in the illusion engine.
8. The apparatus of claim 7, wherein the data scheduling module is further configured to obtain a current node error at the current node corresponding level according to the area of the mesh model and the resolution of the texture picture as:
wherein NGPE represents the current node error, 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, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111008307.2A CN113628331B (en) | 2021-08-30 | 2021-08-30 | Data organization and scheduling method for photogrammetry model in illusion engine |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111008307.2A CN113628331B (en) | 2021-08-30 | 2021-08-30 | Data organization and scheduling method for photogrammetry model in illusion engine |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113628331A true CN113628331A (en) | 2021-11-09 |
CN113628331B CN113628331B (en) | 2023-06-13 |
Family
ID=78388635
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111008307.2A Active CN113628331B (en) | 2021-08-30 | 2021-08-30 | Data organization and scheduling method for photogrammetry model in illusion engine |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113628331B (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114170394A (en) * | 2021-12-03 | 2022-03-11 | 北京数字政通科技股份有限公司 | Display optimization method and device of mass oblique data on Web end |
CN114494623A (en) * | 2022-01-24 | 2022-05-13 | 北京中航双兴科技有限公司 | LOD-based terrain rendering method and device |
CN114549772A (en) * | 2022-02-24 | 2022-05-27 | 中铁二院工程集团有限责任公司 | Multi-source three-dimensional model fusion processing method and system based on engineering independent coordinate system |
CN115129291A (en) * | 2022-08-31 | 2022-09-30 | 中国人民解放军国防科技大学 | Three-dimensional oblique photography measurement model visualization optimization method, device and equipment |
CN116416387A (en) * | 2023-06-12 | 2023-07-11 | 中国电建集团昆明勘测设计研究院有限公司 | OSGB three-dimensional model rapid top layer reconstruction method |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8970583B1 (en) * | 2012-10-01 | 2015-03-03 | Google Inc. | Image space stylization of level of detail artifacts in a real-time rendering engine |
CN111179414A (en) * | 2019-12-30 | 2020-05-19 | 中国电力企业联合会电力建设技术经济咨询中心 | Terrain LOD generation method |
-
2021
- 2021-08-30 CN CN202111008307.2A patent/CN113628331B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8970583B1 (en) * | 2012-10-01 | 2015-03-03 | Google Inc. | Image space stylization of level of detail artifacts in a real-time rendering engine |
CN111179414A (en) * | 2019-12-30 | 2020-05-19 | 中国电力企业联合会电力建设技术经济咨询中心 | Terrain LOD generation method |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114170394A (en) * | 2021-12-03 | 2022-03-11 | 北京数字政通科技股份有限公司 | Display optimization method and device of mass oblique data on Web end |
CN114494623A (en) * | 2022-01-24 | 2022-05-13 | 北京中航双兴科技有限公司 | LOD-based terrain rendering method and device |
CN114549772A (en) * | 2022-02-24 | 2022-05-27 | 中铁二院工程集团有限责任公司 | Multi-source three-dimensional model fusion processing method and system based on engineering independent coordinate system |
CN115129291A (en) * | 2022-08-31 | 2022-09-30 | 中国人民解放军国防科技大学 | Three-dimensional oblique photography measurement model visualization optimization method, device and equipment |
CN116416387A (en) * | 2023-06-12 | 2023-07-11 | 中国电建集团昆明勘测设计研究院有限公司 | OSGB three-dimensional model rapid top layer reconstruction method |
CN116416387B (en) * | 2023-06-12 | 2023-08-11 | 中国电建集团昆明勘测设计研究院有限公司 | OSGB three-dimensional model rapid top layer reconstruction method |
Also Published As
Publication number | Publication date |
---|---|
CN113628331B (en) | 2023-06-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113628331B (en) | Data organization and scheduling method for photogrammetry model in illusion engine | |
CN113628314B (en) | Visualization method, device and equipment for photographic measurement model in illusion engine | |
CN110543716B (en) | Three-dimensional overhead cable hierarchical power grid optimization method, device and computer equipment | |
CN110706341B (en) | High-performance rendering method and device of city information model and storage medium | |
CN110442393B (en) | Map dynamic loading method, computer storage medium and electronic device | |
CN103970518B (en) | A kind of the 3D rendering method and device of window logic | |
WO2024108975A1 (en) | Slicing method for spatial model data | |
CN114596423A (en) | Model rendering method and device based on virtual scene gridding and computer equipment | |
CN112843700B (en) | Terrain image generation method and device, computer equipment and storage medium | |
US20230351696A1 (en) | Data processing method and apparatus, device, computer-readable storage medium, and computer program product | |
CN115033972B (en) | Method and system for unitizing building main body structures in batches and readable storage medium | |
CN117056626A (en) | Map preview method and device | |
CN114170394B (en) | Method and device for optimizing display of massive inclined data on Web end | |
CN116030176A (en) | Three-dimensional model rendering method, device, equipment and medium based on cluster division | |
Nguyen et al. | Progressive streaming and massive rendering of 3D city models on web-based virtual globe | |
CN114494623A (en) | LOD-based terrain rendering method and device | |
Jiang et al. | A large-scale scene display system based on webgl | |
CN117237503B (en) | Geographic element data accelerated rendering and device | |
CN116883575B (en) | Building group rendering method, device, computer equipment and storage medium | |
WO2023221683A1 (en) | Image rendering method and apparatus, device, and medium | |
CN112446959B (en) | Oblique photography model optimization method | |
CN116958408A (en) | Three-dimensional scene construction method, device, equipment, medium and program product | |
CN116821385A (en) | Layer indexing method and device for live-action three-dimensional image and electronic equipment | |
Zhang et al. | Real-time rendering of large-scale terrain based on GPU | |
Dai et al. | Fast rendering of massive textured terrain data |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |