CN114494641B - Three-dimensional model light weight method and device - Google Patents
Three-dimensional model light weight method and device Download PDFInfo
- Publication number
- CN114494641B CN114494641B CN202210013748.XA CN202210013748A CN114494641B CN 114494641 B CN114494641 B CN 114494641B CN 202210013748 A CN202210013748 A CN 202210013748A CN 114494641 B CN114494641 B CN 114494641B
- Authority
- CN
- China
- Prior art keywords
- dimensional model
- model
- plane
- block
- space
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 59
- 230000011218 segmentation Effects 0.000 claims abstract description 38
- 238000012216 screening Methods 0.000 claims abstract description 26
- 238000004364 calculation method Methods 0.000 claims abstract description 10
- 230000000903 blocking effect Effects 0.000 claims abstract description 4
- 239000013598 vector Substances 0.000 claims description 13
- 238000004422 calculation algorithm Methods 0.000 claims description 8
- 238000003064 k means clustering Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 abstract description 5
- 239000011159 matrix material Substances 0.000 description 7
- 238000013507 mapping Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000004590 computer program Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- KLDZYURQCUYZBL-UHFFFAOYSA-N 2-[3-[(2-hydroxyphenyl)methylideneamino]propyliminomethyl]phenol Chemical compound OC1=CC=CC=C1C=NCCCN=CC1=CC=CC=C1O KLDZYURQCUYZBL-UHFFFAOYSA-N 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 201000001098 delayed sleep phase syndrome Diseases 0.000 description 1
- 208000033921 delayed sleep phase type circadian rhythm sleep disease Diseases 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- 239000013585 weight reducing agent Substances 0.000 description 1
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
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
- G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Graphics (AREA)
- Software Systems (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- Architecture (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Processing Or Creating Images (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a three-dimensional model light-weight 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 topological continuous triangular grid model; performing surface segmentation according to the plane characteristics of the triangular mesh model to obtain segmented flat surface areas after the whole three-dimensional model is segmented; carrying out plane difference degree calculation on adjacent division surfaces according to the division flat surface areas to obtain a combined block; screening geometric feature points in boundary line nodes according to boundary lines of the combined blocks, and taking a space surface formed by the geometric feature points as a lightweight 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 light-weight blocking surface to obtain a light-weight 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 high-efficiency loading of the three-dimensional model.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a three-dimensional model light-weight method and device.
Background
With the development of network technology and computer technology, three-dimensional visualization technology has also been rapidly developed and has been widely used. For example, urban three-dimensional models are important components 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 acquired three-dimensional models are higher and higher in precision, and the display of the three-dimensional models has higher requirements on hardware performance such as computing performance, physical storage space, memory space, GPU rendering capability and the like, and can only be carried out by means of a personal computer with better hardware conditions in a long time. In addition, since the three-dimensional model has large data and long transmission time, the three-dimensional model is displayed in a visual interface in a stuck manner, and therefore, the three-dimensional model needs to be subjected to light weight processing.
Disclosure of Invention
The invention aims to provide a three-dimensional model light-weight method, which is used for improving the simplification efficiency and the simplification quality of a three-dimensional model and realizing 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 three-dimensional model light-weight method, including:
reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topological continuous triangular grid model;
performing surface segmentation according to the plane characteristics of the triangular mesh model to obtain segmented flat surface areas of the whole three-dimensional model after segmentation;
performing plane difference calculation on the adjacent division surfaces according to the block flattening surface areas, and combining the adjacent division surfaces with the plane difference within a preset threshold range to obtain a combined block;
screening geometric feature points in boundary line nodes according to boundary lines of the combined blocks, and taking a space surface formed by the geometric feature points as a lightweight 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 light-weight blocking surface to obtain a light-weight three-dimensional model.
Preferably, the reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topological continuous triangular grid model includes:
and acquiring 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 triangular grid model with continuous topology.
Preferably, the surface segmentation is performed according to the planar features of the triangular mesh model to obtain a segmented flat surface area after the whole three-dimensional model is segmented, which comprises:
and determining a local fitting plane of the triangular mesh model based on a K-means clustering algorithm, and classifying the vertices of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented.
Preferably, the calculating the plane difference degree of the adjacent division planes according to the block flat plane area, and merging the adjacent division planes with the plane difference degree within a preset threshold range to obtain a merged block, includes:
calculating the included angle between the triangular grid normal vectors of the three-dimensional model segmentation part according to the curvature of the boundary connection part of the three-dimensional model segmentation part to obtain the plane difference degree;
and merging the adjacent dividing surfaces with smaller plane difference degree to obtain a merged block.
Preferably, the filtering the geometric feature points in the boundary line nodes according to the boundary line of the merged block, and taking the space surface formed by the geometric feature points as the 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 part of nodes of the boundary line of the model, screening geometrical characteristic points in the boundary line nodes, and taking a space plane formed by the geometrical characteristic points as a lightweight block plane of the model.
The embodiment of the invention also provides a three-dimensional model light device, which comprises:
the tile merging module is used for reconstructing the three-dimensional model according to tile data of the three-dimensional model to obtain a triangular grid model with continuous topology;
the plane segmentation module is used for carrying out plane segmentation according to the plane characteristics of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented;
the block merging module is used for carrying out plane difference degree calculation on the adjacent division surfaces according to the block flattening surface areas, merging the adjacent division surfaces with the plane difference degree within a preset threshold range, and obtaining a merged block;
the feature screening module is used for screening geometric feature points in boundary line nodes according to the boundary lines of the combined blocks, and taking a space surface formed by the geometric feature points as a lightweight 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 light-weight block surface to obtain a light-weight three-dimensional model.
Preferably, the tile merging module is further configured to:
and acquiring 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 triangular grid model with continuous topology.
Preferably, the planar segmentation module is further configured to:
and determining a local fitting plane of the triangular mesh model based on a K-means clustering algorithm, and classifying the vertices of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented.
Preferably, the block merging module is further configured to:
calculating the included angle between the triangular grid normal vectors of the three-dimensional model segmentation part according to the curvature of the boundary connection part of the three-dimensional model segmentation part to obtain the plane difference degree;
and merging the adjacent dividing surfaces with smaller plane difference degree 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 part of nodes of the boundary line of the model, screening geometrical characteristic points in the boundary line nodes, and taking a space plane formed by the geometrical characteristic points as a lightweight block plane of the model.
Compared with the prior art, the invention has the following beneficial effects:
according to the three-dimensional model light-weight method, the three-dimensional model is reconstructed through tile data of the three-dimensional model, plane segmentation is carried out according to plane characteristics of the triangular mesh model, plane difference degree calculation is carried out on adjacent segmentation planes, geometrical characteristic points in boundary line nodes are screened, a space plane formed by the geometrical characteristic points is used as a light-weight block plane of the three-dimensional model, a space orthographic projection method is adopted to generate new textures, and texture mapping from a texture picture to the simplified three-dimensional model is achieved. The invention can improve the simplification efficiency and the simplification quality of the three-dimensional model, and realize the optimized storage and the high-efficiency loading of the three-dimensional model.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed 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 that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a three-dimensional model lightweight method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating extraction of adjacent boundaries before merging of triangle tiles according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a triangle tile merging according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a three-dimensional model lightweight device 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 following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the step numbers used herein are for convenience of description only and are not limiting as to the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification 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 stated 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 any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1, fig. 1 is a flow chart of a three-dimensional model lightening method according to an embodiment of the invention. In this embodiment, the three-dimensional model light weight method includes the steps of:
s110, reconstructing the three-dimensional model according to tile data of the three-dimensional model to obtain a topological continuous triangular grid model;
s120, carrying out surface segmentation according to the plane characteristics of the triangular mesh model to obtain segmented flat surface areas of the whole three-dimensional model after segmentation;
s130, carrying out plane difference degree calculation on adjacent divided surfaces according to the block flattening areas, and combining the adjacent divided 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 boundary lines of the combined blocks, and taking a space surface formed by the geometric feature points as a lightweight block surface of a three-dimensional model;
and S150, generating new textures by adopting a space orthographic projection method according to the space region range covered by the light-weight block surface, so as to obtain a light-weight three-dimensional model.
In an embodiment, step S110, reconstructing the three-dimensional model according to tile data of the three-dimensional model to obtain a topologically continuous triangular mesh model, includes: and acquiring 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 triangular grid model with continuous topology.
Specifically, in some embodiments, a tile pyramid level of a desired accuracy is first determined based on a tilted photogrammetry three-dimensional model tile pyramid model; then grouping according to the spatial position relationship, two adjacent sub-tiles are grouped in space, and adjacent edges of each group of sub-tiles are extracted, see fig. 2. And comparing the respective vertex numbers in adjacent edges of the adjacent sub-tiles, and when the vertex numbers are different, performing edge folding operation on the edges with more numbers, and reducing the vertex numbers in the edges until the vertex numbers on the two adjacent edges are equal. Finally, adjacent vertexes are sequentially and alternately selected as a triangle grid connected with the triangle tiles according to the space sequence, all vertex coordinates, normal vectors and texture information in the two tiles are combined into one file, and the combination of the two tiles is completed, as shown in fig. 3. Likewise, the above procedure is iterated until all tiles are merged into an integral triangular grid.
In a certain embodiment, step S120, performing surface segmentation according to the planar features of the triangular mesh model to obtain a segmented flat surface area after the whole three-dimensional model is segmented, includes: and determining a local fitting plane of the triangular mesh model based on a K-means clustering algorithm, and classifying the vertices of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented.
Specifically, in some embodiments, firstly, classifying the triangular mesh vertices by using a K-means clustering method, then fitting the whole three-dimensional model by using K planes, and determining each fitting plane through the three-dimensional space position of the three-dimensional model vertices to ensure that the distance from each vertex to the fitting plane to which each vertex belongs is sufficiently close. The specific method for determining the fitting plane of the triangular mesh vertex is as follows:
assume that the fitted plane objective function of the triangle mesh vertices of a certain area is:
ax+by+cz＝d
wherein ω= (a, b, c) is a vector and satisfies: i omega I 2 ＝1。
Centralizing the vertex set:
the sum of squares of the distances from each model vertex in the class cluster to the fitting plane is:
x i ，y i ，z i for the space coordinates of the model vertexes, according to the plane fitting target, the minimum value should be taken, and the Lagrange multiplier method is used for obtaining:
obtaining the deviation guide:
namely:
wherein,,
for matrix X T X performs eigenvalue decomposition to obtain eigenvalue lambda 1 ≥λ 2 ≥λ 3 Obtaining a characteristic vector v 1 ，v 2 ，v 3 . V taking 3 In order to fit the normal vector of the plane,
to fit a point on a plane.
The fitting plane equation is:
defining a distance function:
current cluster C j Number of middle vertices s<3, the distance is measured as the Euclidean distance (euclidean distance)
dist ed (p i ，u j )＝||p i -u j || 2
Current cluster C j When the number s of middle top points is more than or equal to 3, the distance is measured to obtain a weighted distance (weight distance), and the distance between the top point of the model and a fitting plane dist is calculated pa The weighted distance is then calculated:
dist wd (p i ，u j )＝w 1 ·dist pa +w 2 ·||p i -u j || 2
wherein the method comprises the steps of
w 1 And w 2 As a weighting coefficient, w 1 ≥0，w 2 ≥0，w 1 +w 2 ＝1。
For a given one of the noise grid models d= { p 1 ，p 2 ，…，p m Selecting k model vertexes { u } from the grid model 1 ，u 2 ，…，u k Using the } as an initial clustering seed point, and obtaining a final clustering result C= { C by the following clustering algorithm 1 ，C 2 ，…，C k }。
The specific process comprises the following steps:
in an embodiment, step S130, performing a plane difference calculation on the adjacent division planes according to the block flat area, and merging the adjacent division planes with the plane difference within a preset threshold range to obtain a merged block, where the step includes: calculating the included angle between the triangular grid normal vectors of the three-dimensional model segmentation part according to the curvature of the boundary connection part of the three-dimensional model segmentation part to obtain the plane difference degree; and merging the adjacent dividing surfaces with smaller plane difference degree to obtain a merged block.
In the present embodiment, the calculation of the plane difference degree includes: calculating an included angle theta between normal vectors of the triangular grids at the dividing position of the model, setting a threshold angle delta (delta=15°), and if theta < delta, marking the included angle of the two side blocks as a small curvature edge within a reasonable threshold range, otherwise marking as a large curvature edge. And finally, counting the connection part of the block boundaries, wherein the occupancy ratio u of the large curvature edge between the adjacent triangular tiles is the plane difference degree. Generally, in order to obtain a block after merging, adjacent dividing planes with smaller plane difference are selected for merging. Preferably, if u is less than 75%, the two partitions are combined and if greater than 75% are considered to be independent two regions.
Specifically, in some embodiments, through step S120, the model mesh cluster segmentation method divides the oblique photogrammetry three-dimensional model D into k block meshes, C respectively segm ＝{C 1 ,C 2 ,…,C k }. In order to ensure the rationality of model segmentation, when a model grid is selected to cluster seed points, the sampling density of the seed points is larger, so that the segmented model blocks are excessive, and a large number of finely crushed model blocks exist. And the segmented model blocks are required to be combined, so that the segmented blocks are reduced.
Considering plane properties and curved surface properties of the three-dimensional model, the model blocks take the curvature of the connection of the boundary of the model blocks as a measurement standard. And calculating an included angle theta between normal vectors of the triangular grids at the dividing position of the model, setting a threshold delta, and if theta is smaller than delta, setting the included angles of the blocks at two sides within a reasonable threshold range, wherein the smaller curvature is indicated, and otherwise, the larger curvature difference is indicated. And finally, counting the connection parts of all the block boundaries, wherein the included angle between the adjacent triangular tiles is smaller than the duty ratio of the threshold delta, if the included angle is smaller than 75%, merging the two blocks, and if the included angle is larger than 75%, considering the two blocks as independent two areas. The specific implementation mode of the region merging algorithm comprises the following steps:
in an embodiment, step S140, according to the boundary line of the merged block, filters geometric feature points in the boundary line node, and uses a space plane formed by the geometric feature points as a lightweight block plane of the three-dimensional model, including: and selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of part of nodes of the boundary line of the model, screening geometrical characteristic points in the boundary line nodes, and taking a space plane formed by the geometrical characteristic points as a lightweight block plane of the model.
Specifically, in some embodiments, after the block models are combined, a large number of nodes exist at the block boundaries, most of the nodes are redundant boundary points, and the boundary points need to be screened, so that the geometric feature points of the boundary points are reserved. Considering the space characteristic attribute of the triangular mesh, firstly extracting the boundary line of the triangular mesh, then selecting the geometric characteristic point of each point in the boundary by using a mobile screening method, and finally only retaining the selected geometric characteristic point.
When judging whether the current vertex is a geometric feature point by using a mobile screening method, determining a nearest space straight line according to the space coordinates of the current vertex and the first two points adjacent to the topology and the last two points adjacent to the topology on the boundary line.
Let a straight line in the triangular mesh space pass through a point (x 0 ，y 0 ，z 0 ) The spatial linear standard equation is:
the finishing method can obtain:
wherein:
the above formula is two space plane equations, a unique straight line is determined by space plane intersection, a space fitting straight line is determined, the method can be converted into the determination of two space fitting planes, and the converted solving targets are the determination parameters a, b, c and d, so that the Euclidean distance from each discrete point in the grid space to the two space planes is minimum.
Expressed in matrix form as:
assume that
The above equation is converted into an error matrix equation:
namely: v=ωx-b
Wherein:
since there are increments in three directions of the grid boundary point coordinates x, y and z, the matrix ω contains the coordinate variable z, which contains random errors, so the error matrix equation V is an equation with errors in the coefficient matrix.
Introducing a adjustment criterion on the basis of formula (1):
substituting the formula (1) into the formula, deriving each element in the matrix omega and the parameter vector X, and obtaining an iteration equation by dividing the equation into two types:
wherein,,
the specific solving process comprises the following steps:
after the space linear fitting equation of the selected vertex is solved, judging whether the vertex is a characteristic point of the block grid model according to the relative distance between the vertex and the 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 spatial linear fitting boundary contour points, the feature points are also used as the feature points of adjacent segmentation surfaces after being selected as the model feature points in one model segmentation surface in order to avoid the fracture of the simplified model.
The specific implementation method comprises the following steps:
in a certain embodiment, in step S150, a spatial orthographic projection method is used to generate a new texture according to the spatial region covered by the lightweight block surface of the model, so as to realize texture mapping after model triangle mesh simplification.
Specifically, in some embodiments, the texture mapping is to calculate the texture coordinates (u, v) of the texture map on the texture picture according to the spatial coordinates (x, y, z) of the three-dimensional model by using a function, and take out the corresponding texture values by using the texture coordinates to render the texture values into the three-dimensional model. It is therefore necessary to determine the mapping function F such that F (x, y, z) → (u, v).
In the original three-dimensional model, each model space point (x i ，y i ，z i ) All have a unique corresponding texture coordinate (u i ，v i ). On the basis of maintaining the original model texture, orthographic projection is carried out on points positioned in the range of the characteristic contour surface according to the spatial range covered by the characteristic contour surface (based on the normal projection direction of the fitting plane of the characteristic contour line), and the texture coordinates corresponding to the points are unchanged. And projecting the vertexes of the original model to the characteristic contour surfaces to obtain texture coordinates corresponding to the simplified three-dimensional model, and realizing texture mapping from the texture picture to the simplified three-dimensional model. Namely: f (F) pro (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 light-weight device according to an embodiment of the invention. In this embodiment, the three-dimensional model light weight 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 triangular grid model with continuous topology;
the plane segmentation module 220 is configured to perform plane segmentation according to the plane characteristics of the triangular mesh model, so as to obtain a segmented flat area after the whole three-dimensional model is segmented;
the block merging module 230 is configured to perform plane difference calculation on the adjacent division planes according to the block flat plane area, and merge the adjacent division planes with the plane difference within a preset threshold range to obtain a merged block;
the feature screening module 240 is configured to screen geometric feature points in boundary line nodes according to boundary lines of the combined blocks, and take a space surface formed by the geometric feature points as a lightweight block surface of the three-dimensional model;
and the space projection module 250 is configured to generate a new texture by using a space orthographic projection method according to the space region coverage of the light-weight blocking surface, so as to obtain a light-weight three-dimensional model.
In one embodiment, tile merge module 210 is further configured to: and acquiring 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 triangular grid model with continuous topology.
In an embodiment, the plane splitting module 220 is further configured to: and determining a local fitting plane of the triangular mesh model based on a K-means clustering algorithm, and classifying the vertices of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented.
In one embodiment, the block merging module 230 is further configured to: calculating the included angle between the triangular grid normal vectors of the three-dimensional model segmentation part according to the curvature of the boundary connection part of the three-dimensional model segmentation part to obtain the plane difference degree; and merging the adjacent dividing surfaces with smaller plane difference degree to obtain a merged block.
In one embodiment, the feature screening 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 part of nodes of the boundary line of the model, screening geometrical characteristic points in the boundary line nodes, and taking a space plane formed by the geometrical characteristic points as a lightweight block plane of the model.
For the specific limitation of the three-dimensional model light-weight device, reference may be made to the above limitation of the three-dimensional model light-weight method, and the description thereof will not be repeated here. The above-described respective modules in the three-dimensional model light-weight device may be realized in whole or in part by software, hardware, or a combination 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.
Referring to fig. 5, an embodiment of the present invention provides a computer terminal device including one or more processors and a memory. The memory is coupled to the processor for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the three-dimensional model lightweight method as in any of the embodiments described above.
The processor is used for controlling the whole operation of the computer terminal equipment so as to complete all or part of the steps of the three-dimensional model light weight method. The memory is used to store various types of data to support operation at the computer terminal device, which 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 (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), 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 (Application Specific Integrated Circuit, abbreviated as ASIC), digital signal processor (Digital Signal Processor, abbreviated as DSP), digital signal processing device (Digital Signal Processing Device, abbreviated as DSPD), programmable logic device (Programmable Logic Device, abbreviated as PLD), field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), controller, microcontroller, microprocessor, or other electronic component for performing the three-dimensional model light-weight method described above and achieving technical effects consistent with the method described above.
In another exemplary embodiment, a computer readable storage medium comprising a computer program is also provided, which when executed by a processor, implements the steps of the three-dimensional model weight reduction method in any of the embodiments described above. For example, the computer readable storage medium may be the above memory including the computer program, and the computer program may be executed by a processor of the computer terminal device to perform the above three-dimensional model light weight method, and achieve the technical effects consistent with the above method.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (9)
1. A method for lightening a three-dimensional model, comprising:
reconstructing the three-dimensional model according to the tile data of the three-dimensional model to obtain a topological continuous triangular grid model;
performing surface segmentation according to the plane characteristics of the triangular mesh model to obtain segmented flat surface areas of the whole three-dimensional model after segmentation;
performing plane difference calculation on the adjacent division surfaces according to the block flattening surface areas, and combining the adjacent division surfaces with the plane difference within a preset threshold range to obtain a combined block;
and screening geometrical feature points in boundary line nodes according to boundary lines of the combined blocks, and taking a space surface formed by the geometrical feature points as a lightweight block surface of a three-dimensional model, wherein the method comprises the following steps of: selecting and judging nodes in the block boundary based on a mobile screening method, calculating a space fitting straight line of part of nodes of the boundary line of the model, screening geometric feature points in the boundary line nodes, and taking a space plane formed by the geometric feature points as a lightweight block plane of the model;
and generating new textures by adopting a space orthographic projection method according to the space region range covered by the light-weight blocking surface to obtain a light-weight three-dimensional model.
2. The method for lightening a three-dimensional model according to claim 1, wherein reconstructing the three-dimensional model according to tile data of the three-dimensional model to obtain a topologically continuous triangular mesh model comprises:
and acquiring 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 triangular grid model with continuous topology.
3. The method for lightening a three-dimensional model according to claim 1, wherein the performing surface segmentation according to the planar features of the triangular mesh model to obtain segmented flat surface areas after the whole three-dimensional model segmentation comprises:
and determining a local fitting plane of the triangular mesh model based on a K-means clustering algorithm, and classifying the vertices of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented.
4. The method for lightening a three-dimensional model according to claim 1, wherein the calculating the plane difference of the adjacent divided surfaces according to the block flattening area, and combining the adjacent divided surfaces with the plane difference within a preset threshold range to obtain a combined block comprises:
calculating the included angle between the triangular grid normal vectors of the three-dimensional model segmentation part according to the curvature of the boundary connection part of the three-dimensional model segmentation part to obtain the plane difference degree;
and merging the adjacent dividing surfaces with smaller plane difference degree to obtain a merged block.
5. A three-dimensional model lightweight device, comprising:
the tile merging module is used for reconstructing the three-dimensional model according to tile data of the three-dimensional model to obtain a triangular grid model with continuous topology;
the plane segmentation module is used for carrying out plane segmentation according to the plane characteristics of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented;
the block merging module is used for carrying out plane difference degree calculation on the adjacent division surfaces according to the block flattening surface areas, merging the adjacent division surfaces with the plane difference degree within a preset threshold range, and obtaining a merged block;
the feature screening module is used for screening geometric feature points in boundary line nodes according to the boundary lines of the combined blocks, and taking a space surface formed by the geometric feature points as a lightweight 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 light-weight block surface to obtain a light-weight three-dimensional model.
6. The three-dimensional model lightweight device of claim 5, wherein the tile merge module is further configured to:
and acquiring 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 triangular grid model with continuous topology.
7. The three-dimensional model lightweight device as defined in claim 5, wherein the planar segmentation module is further configured to:
and determining a local fitting plane of the triangular mesh model based on a K-means clustering algorithm, and classifying the vertices of the triangular mesh model to obtain a segmented flat area after the whole three-dimensional model is segmented.
8. The three-dimensional model lightweight device according to claim 5, wherein the block merging module is further configured to:
calculating the included angle between the triangular grid normal vectors of the three-dimensional model segmentation part according to the curvature of the boundary connection part of the three-dimensional model segmentation part to obtain the plane difference degree;
and merging the adjacent dividing surfaces with smaller plane difference degree to obtain a merged block.
9. The three-dimensional model lightweight device of claim 5, 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 part of nodes of the boundary line of the model, screening geometrical characteristic points in the boundary line nodes, and taking a space plane formed by the geometrical characteristic points as a lightweight block plane of the model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210013748.XA CN114494641B (en) | 2022-01-06 | 2022-01-06 | Three-dimensional model light weight method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210013748.XA CN114494641B (en) | 2022-01-06 | 2022-01-06 | Three-dimensional model light weight method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114494641A CN114494641A (en) | 2022-05-13 |
| CN114494641B true CN114494641B (en) | 2023-04-28 |
Family
ID=81509473
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210013748.XA Active CN114494641B (en) | 2022-01-06 | 2022-01-06 | Three-dimensional model light weight method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114494641B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116402988B (en) * | 2023-05-11 | 2023-12-19 | 北京冰河起源科技有限公司 | Three-dimensional model processing method, device and storage medium |
| CN117807689B (en) * | 2024-03-01 | 2024-04-30 | 烟台大学 | Building engineering data processing method and system based on BIM |
| CN118279417B (en) * | 2024-06-04 | 2024-08-13 | 湖南科技大学 | Data encryption compression method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113838212A (en) * | 2021-09-22 | 2021-12-24 | 杭州趣村游文旅集团有限公司 | Block splicing method of digital country three-dimensional model |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101582173B (en) * | 2009-06-24 | 2012-07-11 | 中国石油天然气集团公司 | Block model building method for complex geological structure |
| CN107679333A (en) * | 2017-10-19 | 2018-02-09 | 大连理工大学 | A kind of method of two-dimensional topology optimum results geometry reconstruction |
| CN112734930B (en) * | 2020-12-30 | 2024-06-04 | 长沙眸瑞网络科技有限公司 | Three-dimensional model light weight method, system, storage medium and image processing device |
| CN113379924B (en) * | 2021-06-30 | 2023-06-09 | 广东三维家信息科技有限公司 | Three-dimensional model simplification method, device and storage medium |
| CN113658327A (en) * | 2021-08-10 | 2021-11-16 | 煤炭科学研究总院 | Method and device for lightening coal mine three-dimensional model data |
-
2022
- 2022-01-06 CN CN202210013748.XA patent/CN114494641B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113838212A (en) * | 2021-09-22 | 2021-12-24 | 杭州趣村游文旅集团有限公司 | Block splicing method of digital country three-dimensional model |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114494641A (en) | 2022-05-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114494641B (en) | Three-dimensional model light weight method and device | |
| CN108961411B (en) | Method for simplifying complex three-dimensional building model by keeping appearance characteristics | |
| CN113781667B (en) | Three-dimensional structure simplified reconstruction method and device, computer equipment and storage medium | |
| Ji et al. | A novel simplification method for 3D geometric point cloud based on the importance of point | |
| CN107123164B (en) | Three-dimensional reconstruction method and system for keeping sharp features | |
| WO2022016310A1 (en) | Point cloud data-based three-dimensional reconstruction method and apparatus, and computer device | |
| JP2013507679A (en) | Method and system capable of 3D printing of 3D object model | |
| CN111581776B (en) | Iso-geometric analysis method based on geometric reconstruction model | |
| CN116071519B (en) | Image processing method and device for generating grid model based on harmonic mapping | |
| US9922458B2 (en) | Methods and systems for generating polycube segmentations from input meshes of objects | |
| CN115082699B (en) | Contour shape extraction method and device, electronic equipment and storage medium | |
| CN101853525B (en) | Mesh segmentation based simplification method for preserving details of textured model | |
| CN114611359B (en) | Grid-parameter hybrid model modeling method and system | |
| CN113538689A (en) | Three-dimensional model mesh simplification method based on feature fusion of neural network | |
| CN114332291A (en) | Oblique photography model building outer contour rule extraction method | |
| Katsoulis et al. | A T-splines-based parametric modeller for computer-aided ship design | |
| CN116188716B (en) | Method and device for reconstructing three-dimensional model of irregular complex building | |
| Li et al. | On surface reconstruction: A priority driven approach | |
| CN111028349B (en) | Hierarchical construction method suitable for rapid visualization of massive three-dimensional live-action data | |
| KR20030016477A (en) | Remeshing optimizing method and apparatus for polyhedral surface | |
| Li | A voxel graph-based resampling approach for the aerial laser scanning of urban buildings | |
| Tanaka et al. | Accuracy-based sampling and reconstruction with adaptive grid for parallel hierarchical tetrahedrization | |
| CN117197395B (en) | Curve triangulation method and device, storage medium and computer equipment | |
| Vierjahn et al. | Surface-reconstructing growing neural gas: A method for online construction of textured triangle meshes | |
| JPH11339071A (en) | System for automatic polygon generation from dot group |
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 |