CN114494641A - Three-dimensional model lightweight method and device - Google Patents
Three-dimensional model lightweight method and device Download PDFInfo
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Abstract
The invention discloses a three-dimensional model lightweight method and device, and relates to the technical field of image processing. The method comprises the following steps: reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topologically continuous triangular grid model; performing surface segmentation according to the plane characteristics of the triangular grid model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented; calculating the plane difference of adjacent segmentation surfaces according to the segmentation flat surface area to obtain a combined block; screening geometric feature points in boundary line nodes according to boundary lines of the merged blocks, and taking a space surface formed by the geometric feature points as a light-weight block surface of the three-dimensional model; and generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model. The invention can improve the simplification efficiency and the simplification quality of the three-dimensional model and realize the optimized storage and the efficient loading of the three-dimensional model.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method and a device for lightening a three-dimensional model.
Background
With the development of network technology and computer technology, three-dimensional visualization technology has also been rapidly developed and widely applied. For example, the urban three-dimensional model is an important component in urban digital infrastructure, including urban planning, environmental monitoring, spatial information analysis, and the like. With the continuous development of digital cities and novel mapping technologies, the precision of the obtained three-dimensional models is higher and higher, the display of the three-dimensional models has higher requirements on the hardware performances such as computing performance, physical storage space, memory space, GPU rendering capability and the like, and the three-dimensional models can only be performed by a personal computer with better hardware conditions for a long time. In addition, since the data of the three-dimensional model is large and the transmission time is long, the three-dimensional model is displayed in a visual interface in a stuck state, and therefore the three-dimensional model needs to be lightened.
Disclosure of Invention
The invention aims to provide a three-dimensional model lightweight method to improve the simplification efficiency and the simplification quality of a three-dimensional model and realize the optimized storage and the efficient loading of the three-dimensional model.
In order to achieve the above object, an embodiment of the present invention provides a method for lightening a three-dimensional model, including:
reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topologically continuous triangular grid model;
performing surface segmentation according to the plane characteristics of the triangular grid model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented;
calculating the plane difference degree of the adjacent segmentation surfaces according to the block smooth surface area, and combining the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a combined block;
screening geometric characteristic points in boundary line nodes according to the boundary line of the merged block, and taking a space surface formed by the geometric characteristic points as a light-weight block surface of the three-dimensional model;
and generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model.
Preferably, the reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain the topologically continuous triangular grid model includes:
obtaining tile data in a selected area of the three-dimensional model, and performing model reconstruction on tiles with specified precision levels in the tile data by using a tile merging method to generate a topologically continuous triangular grid model.
Preferably, the surface segmentation is performed according to the plane features of the triangular mesh model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented, including:
and determining a local fitting plane of the triangular grid model based on a K-means clustering algorithm, and classifying the vertexes of the triangular grid to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented.
Preferably, the calculating the plane difference degree of the adjacent segmentation surfaces according to the segmentation flat surface domain, and combining the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a combined block includes:
calculating an included angle between triangular grid normal vectors at the three-dimensional model segmentation position according to the curvature of the three-dimensional model block boundary connection position to obtain plane difference;
and merging the adjacent divided surfaces with smaller plane difference degrees to obtain a merged block.
Preferably, the screening geometric feature points in boundary line nodes according to the boundary line of the merged block, and using a spatial plane formed by the geometric feature points as a lightweight block surface of the three-dimensional model, includes:
and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of partial nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space surface consisting of the geometric feature points as a lightweight block surface of the model.
The embodiment of the present invention further provides a three-dimensional model lightweight device, including:
the tile merging module is used for reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topologically continuous triangular grid model;
the plane segmentation module is used for carrying out plane segmentation according to the plane characteristics of the triangular grid model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented;
the block merging module is used for calculating the plane difference degree of the adjacent segmentation surfaces according to the block smooth surface domain, merging the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a merged block;
the characteristic screening module is used for screening geometric characteristic points in boundary line nodes according to the boundary line of the merged blocks, and taking a space surface formed by the geometric characteristic points as a light-weight block surface of the three-dimensional model;
and the space projection module is used for generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model.
Preferably, the tile merging module is further configured to:
obtaining tile data in a selected area of the three-dimensional model, and performing model reconstruction on tiles with specified precision levels in the tile data by using a tile merging method to generate a topologically continuous triangular grid model.
Preferably, the plane dividing module is further configured to:
and determining a local fitting plane of the triangular grid model based on a K-means clustering algorithm, and classifying the vertexes of the triangular grid to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented.
Preferably, the block merging module is further configured to:
calculating an included angle between triangular grid normal vectors at the three-dimensional model segmentation position according to the curvature of the three-dimensional model block boundary connection position to obtain plane difference;
and merging the adjacent divided surfaces with smaller plane difference degrees to obtain a merged block.
Preferably, the feature screening module is further configured to:
and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of partial nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space surface consisting of the geometric feature points as a lightweight block surface of the model.
Compared with the prior art, the invention has the following beneficial effects:
the three-dimensional model lightweight method provided by the invention has the advantages that the three-dimensional model is reconstructed through tile data of the three-dimensional model, the surface segmentation is carried out according to the plane characteristics of the triangular grid model, the plane difference degree calculation is carried out on the adjacent segmentation surfaces, the geometric characteristic points in the boundary line nodes are screened, the space surface formed by the geometric characteristic points is used as the lightweight block surface of the three-dimensional model, a space orthographic projection method is adopted to generate new textures, and the texture mapping from a texture picture to the simplified three-dimensional model is realized. The invention can improve the simplification efficiency and the simplification quality of the three-dimensional model and realize the optimized storage and the efficient loading of the three-dimensional model.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a three-dimensional model weight reduction method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of extracting neighboring boundaries before merging triangular tiles according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a merged triangle tile according to an embodiment of the present invention;
fig. 4 is a schematic structural view of a three-dimensional model weight reduction apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer terminal device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not used as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic flow chart of a three-dimensional model weight reduction method according to an embodiment of the present invention. In this embodiment, the three-dimensional model weight reduction method includes the steps of:
s110, reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topologically continuous triangular grid model;
s120, performing surface segmentation according to the plane characteristics of the triangular grid model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented;
s130, calculating the plane difference degree of the adjacent segmentation surfaces according to the block smooth surface area, and combining the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a combined block;
s140, screening geometric feature points in boundary line nodes according to the boundary line of the merged blocks, and taking a space surface formed by the geometric feature points as a light-weight block surface of the three-dimensional model;
and S150, generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model.
In one embodiment, step S110 is to reconstruct the three-dimensional model according to the tile data of the three-dimensional model, so as to obtain a topologically continuous triangular mesh model, including: obtaining tile data in a selected area of the three-dimensional model, and performing model reconstruction on tiles with specified precision levels in the tile data by using a tile merging method to generate a topologically continuous triangular grid model.
Specifically, in some embodiments, based on a tilted photogrammetry three-dimensional model tile pyramid model, a level of the tile pyramid of a desired precision is first determined; and then grouping according to the spatial position relationship, grouping every two adjacent sub-tiles in space, and extracting the adjacent edges of each group of sub-tiles, as shown in fig. 2. And comparing the number of vertexes of the adjacent edges of the adjacent sub-tiles, and when the number of the vertexes is different, performing edge folding operation on the edges with more numbers to reduce the number of the vertexes in the edges until the number of the vertexes on the two adjacent edges is equal. And finally, alternately selecting adjacent vertexes in sequence according to the spatial sequence to serve as a connecting triangular grid of the triangular tiles, and combining all vertex coordinates, normal vectors and texture information in the two tiles into a file to complete the combination of the two tiles, as shown in fig. 3. Similarly, the above process is iterated until all tiles are merged into a whole triangular grid.
In one embodiment, step S120, performing surface segmentation according to the planar features of the triangular mesh model to obtain a segmented flat surface domain after the segmentation of the integral three-dimensional model, includes: and determining a local fitting plane of the triangular grid model based on a K-means clustering algorithm, and classifying the vertexes of the triangular grid to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented.
Specifically, in some embodiments, the vertices of the triangular mesh are first classified by K-means clustering, then the entire three-dimensional model is fitted with K planes, and each fitting plane is determined by the three-dimensional spatial position of the vertex of the three-dimensional model, so that the distance between each vertex and the fitting plane to which the vertex belongs is close enough. The specific method for determining the fitting plane of the vertex of the triangular grid is as follows:
assuming that the objective function of the fitting plane of the triangular grid vertex in a certain region is as follows:
ax+by+cz＝d
wherein ω ═ (a, b, c) is a vector and satisfies: | ω | non-calculation2＝1。
Centralizing the vertex set:
the sum of the squares of the distances from each model vertex in the cluster class to the fitting plane is:
xi，yi，ziand (3) according to a plane fitting target, taking the minimum value corresponding to the formula, and obtaining the space coordinate of the model vertex by using a Lagrange multiplier method:
obtaining a partial derivative:
namely:
wherein the content of the first and second substances,
for matrix XTDecomposing the characteristic value of X to obtain the characteristic value lambda1≥λ2≥λ3To obtain a feature vector v1，v2，v3. Get v3To fit the normal vector of the plane,
is a point on the fitted plane.
The fitted plane equation is:
defining a distance function:
current cluster CjNumber of middle vertex s<When 3, measuring the Euclidean distance (eutriean distance)
disted(pi，uj)＝||pi-uj||2
Current cluster CjWhen the number s of the middle vertex points is more than or equal to 3, measuring a 'weighted distance' (weight distance) by using the distance quantity, and calculating the distance dist from the model vertex to the fitting planepaThen, the weighted distance is calculated:
distwd(pi，uj)＝w1·distpa+w2·||pi-uj||2
wherein
w1And w2As a weighting coefficient, w1≥0，w2≥0，w1+w2＝1。
For a given noise mesh model D ═ p1，p2，…，pmSelecting k model vertices { u } from the mesh model1，u2，…，ukUsing the obtained cluster result as an initial cluster seed point, and obtaining a final cluster result C ═ C through the following clustering algorithm1，C2，…，Ck}。
The specific process comprises the following steps:
in one embodiment, step S130, calculating a plane difference degree of adjacent partition surfaces according to the block flat surface region, and merging the adjacent partition surfaces whose plane difference degrees are within a preset threshold range to obtain a merged block, includes: calculating an included angle between triangular grid normal vectors at the three-dimensional model segmentation position according to the curvature of the three-dimensional model block boundary connection position to obtain plane difference; and merging the adjacent divided surfaces with smaller plane difference degrees to obtain a merged block.
In this embodiment, the calculation of the plane difference degree includes: calculating an included angle theta between normal vectors of the triangular grids at the model segmentation part, setting a threshold angle delta (delta is 15 degrees), if theta is smaller than delta, recording the blocked included angle at the two sides as a small curvature side within a reasonable threshold range, and otherwise, recording as a large curvature side. And finally, counting the ratio u of the large curvature edge between the adjacent triangular tiles at the joint of the block boundaries, wherein the u is the plane difference. Generally, to obtain the merged block, the neighboring partition planes with small plane difference are selected for merging. Preferably, if u is less than 75%, the two partitions are combined, and if u is greater than 75%, the two partitions are considered to be two independent regions.
Specifically, in some embodiments, through step S120, the model mesh clustering segmentation method divides the oblique photogrammetry three-dimensional model D into k block meshes Csegm＝{C1,C2,…,Ck}. In order to ensure the reasonability of model segmentation, when the model grid clustering seed points are selected, the sampling density of the seed points is higher, so that the phenomenon that a large number of finely-divided model blocks exist due to too many segmented model blocks can be caused. The divided model blocks need to be merged, so that the divided blocks are reduced.
The model blocks take the curvature of the connection of the boundary of the model blocks as a measurement standard in consideration of the plane property and the curved surface property of the three-dimensional model. Calculating an included angle theta between normal vectors of the triangular grids at the model segmentation part, setting a threshold delta, if the theta is smaller than the delta, indicating that the included angle of the two side blocks is within a reasonable threshold range, and otherwise, indicating that the curvature difference is larger. And finally, counting the ratio of the included angle between adjacent triangular tiles at the boundary connection part of all the blocks, wherein the included angle is smaller than a threshold value delta, if the included angle is smaller than 75%, combining the two blocks, and if the included angle is larger than 75%, considering the two independent areas. The specific implementation mode of the region merging algorithm comprises the following steps:
in one embodiment, step S140, according to the boundary line of the merged block, screening geometric feature points in boundary line nodes, and using a spatial plane formed by the geometric feature points as a light-weighted block surface of the three-dimensional model, includes: and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of partial nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space surface consisting of the geometric feature points as a lightweight block surface of the model.
Specifically, in some embodiments, after the block models are combined, a large number of nodes exist at the block boundary, most of the nodes are redundant boundary points, and the boundary points need to be screened and the geometric feature points of the boundary points are reserved. In consideration of the spatial characteristic attribute of the triangular mesh, firstly, the boundary line of the triangular mesh is extracted, then, the geometric characteristic point selection is carried out on each point in the boundary by using a mobile screening method, and finally, only the selected geometric characteristic point is reserved.
When judging whether the current vertex is a geometric feature point by using a mobile screening method, firstly, a spatial straight line closest to the current vertex and the boundary line needs to be determined according to the space coordinates of the first two points adjacent to the topology and the second two points adjacent to the topology on the current vertex and the boundary line.
Suppose a straight line in the triangular grid space passes through a point (x)0，y0，z0) The standard equation of the space straight line is as follows:
finishing to obtain:
wherein:
the above formula is an equation of two space planes, the space planes intersect to determine a unique straight line, a space fitting straight line is determined, the space fitting straight line can be converted into the determination of the two space fitting planes, and the converted solving target is to determine parameters a, b, c and d, so that the sum of Euclidean distances from each discrete point in the grid space to the two space planes is minimum.
Expressed in matrix form as:
suppose that
Converting the above equation into an error matrix equation:
namely: v ═ ω X-b
Wherein:
because the coordinates x, y and z of the boundary points of the grid are all increased in three directions, the matrix omega contains a coordinate variable z which contains random errors, and the error matrix equation V is an equation of which the coefficient matrix contains errors.
Introducing a balance criterion on the basis of the formula (1):
substituting the formula (1) into the above formula, deriving each element in the matrix omega and the parameter vector X, and obtaining an iterative equation by dividing the equation into two types:
wherein the content of the first and second substances,
the specific solving process comprises the following steps:
and after a space linear fitting equation of the selected vertex is obtained, judging whether the vertex is a characteristic point of the block grid model according to the relative distance between the vertex and a space straight line, and finally forming a simplified model block surface by using a point set of all the characteristic points.
When the feature points of each model segmentation surface are selected by utilizing the space linear fitting boundary contour points, in order to avoid the fracture of the simplified model, the feature points of the adjacent segmentation surfaces are simultaneously formed after the feature points are selected from one model segmentation surface.
The specific implementation method comprises the following steps:
in a certain embodiment, in step S150, a new texture is generated by using a spatial orthographic projection method according to a spatial region range covered by the lightweight block surface of the model, so as to implement texture mapping after the triangular mesh of the model is simplified.
Specifically, in some embodiments, the texture mapping is to calculate the texture coordinates (u, v) of the three-dimensional model on the texture picture by a function according to the spatial coordinates (x, y, z) of the three-dimensional model, and use the texture coordinates to fetch the corresponding texture values and render the texture values into the three-dimensional model. The mapping function F needs to be determined such that F (x, y, z) → (u, v).
In the original three-dimensional model, each modelType space point (x)i，yi，zi) All have a unique corresponding texture coordinate (u)i，vi). On the basis of keeping the original model texture, orthographic projection is carried out on points located in the range of the characteristic contour surface according to the space range covered by the characteristic contour surface (taking the normal projection direction of the characteristic contour line fitting plane as the standard), and the corresponding texture coordinate is unchanged. By projecting the vertex of the original model to the characteristic profile surface, the texture coordinate corresponding to the simplified three-dimensional model is obtained, and the texture mapping from the texture picture to the simplified three-dimensional model is realized. Namely: fpro(x，y，z)→(x′，y′，z′)，F(x′，y′，z′)→(u，v)。
Referring to fig. 4, fig. 4 is a schematic structural diagram of a three-dimensional model weight reduction device according to an embodiment of the present invention. In this embodiment, the three-dimensional model weight reduction device includes:
the tile merging module 210 is configured to reconstruct the three-dimensional model according to tile data of the three-dimensional model, so as to obtain a topologically continuous triangular grid model;
the plane segmentation module 220 is configured to perform plane segmentation according to the plane features of the triangular mesh model to obtain a partitioned flat plane domain of the integral three-dimensional model after segmentation;
the block merging module 230 is configured to perform plane difference degree calculation on adjacent split surfaces according to the block flat surface domain, and merge the adjacent split surfaces with the plane difference degree within a preset threshold range to obtain a merged block;
a feature screening module 240, configured to screen geometric feature points in boundary line nodes according to the boundary line of the merged block, and use a spatial plane formed by the geometric feature points as a lightweight block surface of the three-dimensional model;
and the space projection module 250 is used for generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model.
In a certain embodiment, tile merging module 210 is further configured to: obtaining tile data in a selected area of the three-dimensional model, and performing model reconstruction on tiles with specified precision levels in the tile data by using a tile merging method to generate a topologically continuous triangular grid model.
In an embodiment, the plane segmentation module 220 is further configured to: and determining a local fitting plane of the triangular grid model based on a K-means clustering algorithm, and classifying the vertexes of the triangular grid to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented.
In one embodiment, the block merging module 230 is further configured to: calculating an included angle between triangular grid normal vectors at the three-dimensional model segmentation position according to the curvature of the three-dimensional model block boundary connection position to obtain plane difference; and merging the adjacent divided surfaces with smaller plane difference degrees to obtain a merged block.
In one embodiment, the feature filtering module 240 is further configured to: and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of partial nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space surface consisting of the geometric feature points as a lightweight block surface of the model.
For specific definition of the three-dimensional model weight reducing device, reference may be made to the definition of the three-dimensional model weight reducing method above, and details are not repeated here. The respective blocks in the three-dimensional model lightening device described above may be implemented in whole or in part by software, hardware, and a combination 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.
Referring to fig. 5, an embodiment of the invention provides a computer terminal device, which includes one or more processors and a memory. A memory is coupled to the processor for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement a three-dimensional model weight reduction method as in any of the embodiments described above.
The processor is used for controlling the overall operation of the computer terminal equipment so as to complete all or part of the steps of the three-dimensional model lightweight method. The memory is used to store various types of data to support the operation at the computer terminal device, which data may include, for example, instructions for any application or method operating on the computer terminal device, as well as application-related data. The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
In an exemplary embodiment, the computer terminal Device may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is configured to perform the three-dimensional model weight reduction method and achieve technical effects consistent with the method.
In another exemplary embodiment, there is also provided a computer readable storage medium comprising a computer program which, when executed by a processor, implements the steps of the three-dimensional model weight reduction method in any one of the above embodiments. For example, the computer readable storage medium may be the above-mentioned memory including a computer program, which is executable by a processor of a computer terminal device to perform the above-mentioned three-dimensional model weight reduction method, and achieve the technical effects consistent with the above-mentioned method.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. A method for reducing the weight of a three-dimensional model, comprising:
reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topologically continuous triangular grid model;
performing surface segmentation according to the plane characteristics of the triangular grid model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented;
calculating the plane difference degree of the adjacent segmentation surfaces according to the block smooth surface area, and combining the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a combined block;
screening geometric characteristic points in boundary line nodes according to the boundary line of the merged block, and taking a space surface formed by the geometric characteristic points as a light-weight block surface of the three-dimensional model;
and generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model.
2. The method for reducing the weight of the three-dimensional model according to claim 1, wherein reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain the topologically continuous triangular mesh model comprises:
obtaining tile data in a selected area of the three-dimensional model, and performing model reconstruction on tiles with specified precision levels in the tile data by using a tile merging method to generate a topologically continuous triangular grid model.
3. The method for reducing the weight of the three-dimensional model according to claim 1, wherein the step of performing surface segmentation according to the plane features of the triangular mesh model to obtain the segmented flat surface region after the segmentation of the whole three-dimensional model comprises the following steps:
and determining a local fitting plane of the triangular grid model based on a K-means clustering algorithm, and classifying the vertexes of the triangular grid to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented.
4. The method for reducing the weight of the three-dimensional model according to claim 1, wherein the calculating the plane difference degree of the adjacent segmentation surfaces according to the segmentation flat surface domain, and combining the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a combined block comprises:
calculating an included angle between triangular grid normal vectors at the three-dimensional model segmentation position according to the curvature of the three-dimensional model block boundary connection position to obtain plane difference;
and merging the adjacent partition surfaces with smaller plane difference degrees to obtain a merged block.
5. The method for reducing the weight of a three-dimensional model according to claim 1, wherein the step of screening geometric feature points in boundary line nodes from the boundary lines of the merged blocks and using a spatial plane formed by the geometric feature points as a light-weight block surface of the three-dimensional model comprises the steps of:
and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of partial nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space surface consisting of the geometric feature points as a lightweight block surface of the model.
6. A three-dimensional model weight reduction device is characterized by comprising:
the tile merging module is used for reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topologically continuous triangular grid model;
the plane segmentation module is used for carrying out plane segmentation according to the plane characteristics of the triangular grid model to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented;
the block merging module is used for calculating the plane difference degree of the adjacent segmentation surfaces according to the block smooth surface domain, merging the adjacent segmentation surfaces with the plane difference degree within a preset threshold range to obtain a merged block;
the characteristic screening module is used for screening geometric characteristic points in boundary line nodes according to the boundary line of the merged blocks, and taking a space surface formed by the geometric characteristic points as a light-weight block surface of the three-dimensional model;
and the space projection module is used for generating new textures by adopting a space orthographic projection method according to the space region range covered by the lightweight block surface to obtain a lightweight three-dimensional model.
7. The three-dimensional model weight reduction device according to claim 6, wherein the tile merging module is further configured to:
obtaining tile data in a selected area of the three-dimensional model, and performing model reconstruction on tiles with specified precision levels in the tile data by using a tile merging method to generate a topologically continuous triangular grid model.
8. The three-dimensional model weight reduction device according to claim 6, wherein the plane division module is further configured to:
and determining a local fitting plane of the triangular grid model based on a K-means clustering algorithm, and classifying the vertexes of the triangular grid to obtain a partitioned flat surface domain after the integral three-dimensional model is segmented.
9. The three-dimensional model weight reduction device according to claim 6, wherein the block merging module is further configured to:
calculating an included angle between triangular grid normal vectors at the three-dimensional model segmentation position according to the curvature of the three-dimensional model block boundary connection position to obtain plane difference;
and merging the adjacent divided surfaces with smaller plane difference degrees to obtain a merged block.
10. The three-dimensional model weight reduction device according to claim 6, wherein the feature screening module is further configured to:
and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of partial nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space surface consisting of the geometric feature points as a lightweight block surface of the model.
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