CN117974940A

CN117974940A - Three-dimensional model processing method, device, equipment and medium

Info

Publication number: CN117974940A
Application number: CN202410153759.7A
Authority: CN
Inventors: 赵丹丹
Original assignee: Agricultural Bank of China
Current assignee: Agricultural Bank of China
Priority date: 2024-02-02
Filing date: 2024-02-02
Publication date: 2024-05-03

Abstract

The invention discloses a three-dimensional model processing method, a device, equipment and a medium. The method comprises the following steps: acquiring an original grid model of a three-dimensional object; screening at least one framework vertex from the original vertices of the original grid model, and determining the framework vertex corresponding to each original vertex; for each original vertex, calculating the volume of the vertebral body corresponding to the original vertex according to the original vertex and the skeleton vertex corresponding to the original vertex; aiming at each original vertex, acquiring a Laplace energy equation corresponding to the original vertex; aiming at each original vertex, adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex to obtain an optimized Laplace energy equation corresponding to the original vertex; and obtaining a motion grid model of the three-dimensional object according to the optimized Laplace energy equation corresponding to each original vertex. The technical scheme of the embodiment of the invention can improve the accuracy of processing the three-dimensional model.

Description

Three-dimensional model processing method, device, equipment and medium

Technical Field

The present invention relates to the field of model processing technologies, and in particular, to a method, an apparatus, a device, and a medium for processing a three-dimensional model.

Background

With the continuous development of the deformation technology of the grid model, the technology is applied to the aspects of life of people.

The deformation technology of the grid model can be applied to the image driving aspect of the virtual digital human body in general, and the shape, the expression and the action of the human body are simulated.

However, the current grid deformation technology has the problem of distortion during the application, so that the shape of a model is difficult to be kept unchanged by a virtual digital person in the simulation process, and the problem of model distortion is caused.

Disclosure of Invention

The invention provides a three-dimensional model processing method, a device, equipment and a medium, which are used for improving the accuracy of three-dimensional model processing.

In a first aspect, an embodiment of the present invention provides a three-dimensional model processing method, where the method includes:

acquiring an original grid model of a three-dimensional object;

Screening at least one framework vertex from the original vertices of the original grid model, and determining the framework vertex corresponding to each original vertex;

for each original vertex, calculating the volume of the vertebral body corresponding to the original vertex according to the original vertex and the skeleton vertex corresponding to the original vertex;

Aiming at each original vertex, acquiring a Laplace energy equation corresponding to the original vertex;

aiming at each original vertex, adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex to obtain an optimized Laplace energy equation corresponding to the original vertex;

and obtaining a motion grid model of the three-dimensional object according to the optimized Laplace energy equation corresponding to each original vertex.

In a second aspect, an embodiment of the present invention provides a three-dimensional model processing apparatus, including:

the model acquisition module is used for acquiring an original grid model of the three-dimensional object;

The vertex determining module is used for screening at least one framework vertex from the original vertices of the original grid model and determining the framework vertex corresponding to each original vertex;

The volume calculation module is used for calculating the volume of the vertebral body corresponding to the original vertex according to the original vertex and the skeleton vertex corresponding to the original vertex;

the equation acquisition module is used for acquiring a Laplace energy equation corresponding to each original vertex;

The optimization equation acquisition module is used for adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex aiming at each original vertex to obtain an optimized Laplace energy equation corresponding to the original vertex;

and the motion model acquisition module is used for obtaining a motion grid model of the three-dimensional object according to the optimized Laplace energy equation corresponding to each original vertex.

In a third aspect, an embodiment of the present invention provides a three-dimensional model processing apparatus, including:

At least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the three-dimensional model processing method of any one of the embodiments of the present invention.

In a fourth aspect, embodiments of the present invention provide a computer readable storage medium storing computer instructions for causing a processor to execute a three-dimensional model processing method according to any one of the embodiments of the present invention.

According to the technical scheme, the vertebral body volume corresponding to the original vertex is calculated through the original vertex and the skeleton vertex corresponding to the original vertex, the Laplace energy equation corresponding to the original vertex is obtained, the vertebral body volume corresponding to the original vertex is added into the Laplace energy equation corresponding to the original vertex, the optimized Laplace energy equation corresponding to the original vertex is obtained, the motion grid model of the three-dimensional object is obtained according to the optimized Laplace energy equation corresponding to each original vertex, the motion grid model of the three-dimensional object is obtained through the vertebral body volume compensation Laplace energy equation, the distortion generated by the original grid model of the three-dimensional object in the motion process is reduced through the volume constraint before and after the motion, and the accuracy of the three-dimensional model processing can be improved.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a three-dimensional model processing method provided according to an embodiment of the present invention;

FIG. 2 is a flow chart of a three-dimensional model processing method provided according to an embodiment of the present invention;

FIG. 3 is a flow chart of a three-dimensional model processing method provided according to an embodiment of the present invention;

FIG. 4 is a schematic process diagram of a three-dimensional model processing method according to an embodiment of the present invention;

FIG. 5 is a schematic structural view of a lattice framework according to an embodiment of the present invention;

FIG. 6 is a schematic diagram of a three-dimensional model processing result provided according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of a model structure according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of a model structure provided according to an embodiment of the present invention;

FIG. 9 is a schematic diagram of a three-dimensional model processing apparatus according to an embodiment of the present invention;

fig. 10 is a schematic diagram of a three-dimensional model processing apparatus according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In the technical scheme of the embodiment of the invention, the acquisition, storage, application and the like of the related original grid model and the like all meet the requirements of related laws and regulations, and the prior art is not violated.

Example 1

Fig. 1 is a flowchart of a three-dimensional model processing method according to an embodiment of the present invention. The embodiment of the invention is applicable to the case of three-dimensional model processing, and the method can be executed by a three-dimensional model processing device which can be realized in the form of hardware and/or software.

Referring to the three-dimensional model processing method shown in fig. 1, the method includes:

s101, acquiring an original grid model of the three-dimensional object.

The original mesh model may be an object in three-dimensional space, having a length (height), a width, and a thickness, among others.

Specifically, an original grid model of the three-dimensional object can be obtained through a grid model reading function. Mesh model reading functions include, but are not limited to: readSU2Mesh or stlGetFormat, etc., to which embodiments of the invention are not limited. In computer graphics, three-dimensional objects may be created and represented in a variety of ways, including, but not limited to: three-dimensional modeling software creation or programming language construction. The original mesh model may be a model that approximates a three-dimensional object with a series of polygons (typically triangles) of close size and shape. The original mesh model of a three-dimensional object can be expressed as the following formula:

G＝(V,E)

v is the set of vertices in the original mesh model, E is the set of edges in the original mesh model, where,

V＝[V₁ ^T,V₂ ^T,...,V_n ^T]^T

T is the position of the vertex.

In one example, the original Mesh model of the three-dimensional object is obtained by ReadSU Mesh model read functions.

S102, at least one framework vertex is selected from the original vertices of the original grid model, and the framework vertex corresponding to each original vertex is determined.

Wherein, the original vertex may be a point in the original mesh model where two edges intersect. The lattice framework may be a scaffold that supports the structure, foundation, or contours of a three-dimensional object. The skeleton vertex may be the point on the grid skeleton where two edges meet. Skeleton vertices are obtained by screening among the original vertices. The relation between the original vertex and the skeleton vertex corresponding to the original vertex is many-to-one.

Specifically, at least one original vertex used for composing the original grid model infrastructure is screened from the original vertices of the original grid model, and the original vertices are determined as skeleton vertices. One skeleton vertex may correspond to at least one original vertex. And screening each original vertex in the original grid model to obtain a skeleton vertex, and determining the skeleton vertex corresponding to each original vertex through the distance between each original vertex and each skeleton vertex.

In one example, the original mesh model includes an original vertex 1, an original vertex 2, an original vertex 3, an original vertex 4, an original vertex 5, and an original vertex 6. And screening skeleton vertexes in the original grid model, determining an original vertex 1 as a skeleton vertex a, and determining an original vertex 2 as a skeleton vertex b. And determining framework vertexes corresponding to the original vertexes 1,2 and 3 as framework vertexes a and determining framework vertexes corresponding to the original vertexes 4,5 and 6 as framework vertexes b by calculating the distances between the original vertexes and the framework vertexes.

S103, for each original vertex, calculating the volume of the vertebral body corresponding to the original vertex according to the original vertex and the skeleton vertex corresponding to the original vertex.

The vertebral body volume can be the volume of the vertebral body formed by connecting adjacent and connected original vertexes and skeleton vertexes corresponding to the original vertexes.

Specifically, according to the connection relation between the original vertexes on the original grid model, the needed adjacent and connected original vertexes are selected. The area of the graph formed by the original vertexes is taken as the bottom area of the cone corresponding to the original vertexes. And determining the distance between skeleton vertexes corresponding to the original vertexes as the height of the cone corresponding to the original vertexes, and calculating the volume of the cone corresponding to the original vertexes through the volume and the height of the bottom surface of the cone.

In one example, adjacent and connected primitive vertices are selected to be primitive vertex 1, primitive vertex 2, primitive vertex 3, primitive vertex 4, primitive vertex 5, and primitive vertex 6. The skeleton vertex corresponding to the original vertex 1 is a skeleton vertex a. The area of the shape formed by the original vertex 1, the original vertex 2, the original vertex 3, the original vertex 4, the original vertex 5 and the original vertex 6 is determined as the base area 1, and the base area of the cone 1 corresponding to the original vertex 1 is used as the base area. The distance between the original vertex 1 and the skeleton vertex a is taken as the height of the vertebral body 1. The volume of the vertebral body 1 is calculated by the calculation formula of the volume and height of the bottom surface of the vertebral body.

S104, aiming at each original vertex, acquiring a Laplace energy equation corresponding to the original vertex.

The laplace energy equation corresponding to the original vertex may be a method for calculating the power of the original vertex according to a laplace formula after the spatial position of the original vertex is changed in the deformation process of the original grid model.

Specifically, in the grid deformation process, each original vertex in the original grid model has a corresponding value for doing work. The Laplace energy equation is obtained by the following ways including but not limited to: user input or data query, etc., to which embodiments of the invention are not limited. And substituting the spatial position information of each original vertex into a spatial position parameter item of the Laplace energy equation according to the spatial position information of each original vertex, and obtaining the Laplace energy equation corresponding to each original vertex.

In one example, the original mesh model includes an original vertex 1, an original vertex 2 and an original vertex 3, a laplace energy equation is obtained through data query, and spatial position information of the original vertex 1, the original vertex 2 and the original vertex 3 is respectively brought into the laplace energy equation to obtain laplace energy equations corresponding to the original vertex 1, the original vertex 2 and the original vertex 3.

S105, adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex aiming at each original vertex to obtain the optimized Laplace energy equation corresponding to the original vertex.

The optimized Laplace energy equation may be a calculation method for obtaining the work done by the original vertex through the Laplace energy equation by the vertebral volume compensation optimization.

Specifically, each original vertex of the original grid model has a corresponding cone volume, the Laplace energy equation corresponding to the original vertex is obtained by compensating the Laplace energy equation corresponding to the original vertex through the cone volume, the Laplace energy equation is improved, the sum of acting of the original vertex is equal through volume constraint, and the spatial position of the original vertex is constrained.

In one example, the original mesh model includes an original vertex 1, an original vertex 2, and an original vertex 3, and the laplace energy equations corresponding to the original vertex 1, the original vertex 2, and the original vertex 3 are obtained. And adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex aiming at each original vertex to obtain the optimized Laplace energy equation corresponding to the original vertex 1, the original vertex 2 and the original vertex 3.

And S106, obtaining a motion grid model of the three-dimensional object according to the optimized Laplace energy equation corresponding to each original vertex.

The motion grid model of the three-dimensional object may be a new grid model formed by original vertexes after the spatial position of at least one original vertex in the original grid model of the three-dimensional object is changed.

Specifically, by optimizing the Laplace energy equation corresponding to each original vertex, a new spatial position of each original vertex after the spatial position of the original mesh model is changed by at least one original vertex can be calculated, and a motion mesh model of the three-dimensional object is obtained according to the spatial position of the new original coordinate.

In one example, as shown in fig. 2, the original mesh model includes an original vertex 1, an original vertex 2, and an original vertex 3. The skeleton vertexes corresponding to the original vertexes 1, 2 and 3 are skeleton vertexes 1. And calculating the volume of the vertebral body formed by the original vertex 1, the original vertex 2, the original vertex 3 and the skeleton vertex 1. And obtaining the cone volume corresponding to the original vertex 1, adding the cone volume corresponding to the original vertex 1 into the Laplace energy equation corresponding to the original vertex 1, and obtaining the optimized Laplace energy equation corresponding to the original vertex 1. And obtaining a motion grid model of the three-dimensional object according to the optimized Laplace energy equation.

Optionally, for each original vertex, calculating a volume of the vertebral body corresponding to the original vertex according to the original vertex and the skeleton vertex corresponding to the original vertex, including: selecting a target vertex according to the original vertex of the original grid model; determining a neighborhood vertex corresponding to the target vertex according to the original edge and the target vertex of the original grid model; determining the bottom area of the cone corresponding to the original vertex according to the original edge, the target vertex and the neighborhood vertex corresponding to the target vertex of the original grid model; obtaining skeleton vertexes corresponding to the target vertexes according to the grid skeleton of the original grid model, and determining heights of vertebral bodies corresponding to the original vertexes; and acquiring the volume of the vertebral body corresponding to the target vertex according to the volume and height of the bottom surface of the vertebral body corresponding to the original vertex.

The target vertex may be an original vertex to be subjected to neighborhood vertex search. The original edge may be a connection in the original mesh model that connects the original vertices. The neighborhood vertex may be an original vertex in the original mesh model that is connected adjacent to the target vertex by an original edge. The target vertex corresponds to at least one neighborhood vertex.

Specifically, selecting a target vertex according to an original vertex of an original grid model; determining a neighborhood vertex corresponding to the target vertex according to the original edge and the target vertex of the original grid model; forming a closed graph by the original edge of the original grid model, the target vertex and the neighborhood vertex corresponding to the target vertex, and determining the area of the graph as the bottom area of the cone corresponding to the original vertex; obtaining a framework vertex corresponding to a target vertex according to a grid framework of the original grid model, and determining the distance from the framework vertex to the target vertex as the height of a cone corresponding to the original vertex; and calculating the volume of the cone corresponding to the target vertex according to the volume and height of the cone corresponding to the original vertex. The vertebral volume formula is calculated as follows:

Wherein A is the original edge of the original grid model, the target vertex and the neighborhood vertex corresponding to the target vertex, and the bottom area of the cone corresponding to the original vertex is determined. R is the height of the cone corresponding to the original vertex.

In one example, the original mesh model includes an original vertex 1, an original vertex 2, and an original vertex 3, the original vertex 1 is used as a target vertex, and a neighborhood vertex corresponding to the original vertex 1 is obtained as the original vertex 2 and the original vertex 3 according to a connection relationship between the original vertex and an original edge in the original mesh model. Original vertex 1 and original vertex 2 are connected by original edge 12, original vertex 2 and original vertex 3 are connected by original edge 23, and original vertex 3 and original vertex 1 are connected by original edge 31. The area of the closed graph formed by the original edge 12, the original edge 23, the original edge 31, the original vertex 1, the original vertex 2 and the original vertex 3 is taken as the bottom area 1 of the cone 1 corresponding to the original vertex 1. The skeleton vertex corresponding to the original vertex 1 is the skeleton vertex 1, the distance between the skeleton vertex and the bottom area is taken as the height 1 of the vertebral body 1, and the vertebral body volume corresponding to the original vertex 1 is obtained according to the bottom area 1 and the height 1 of the vertebral body 1.

The bottom area of the cone corresponding to the original vertex is determined through the original side, the target vertex and the neighborhood vertex corresponding to the target vertex of the original grid model, the skeleton vertex corresponding to the target vertex is obtained according to the grid skeleton of the original grid model, the height of the cone corresponding to the original vertex is determined, the cone volume corresponding to the target vertex is obtained according to the bottom area and the height of the cone corresponding to the original vertex, the cone volume corresponding to each original vertex can be obtained, the volume of the original grid model is divided into a plurality of volumes, the data calculation is more accurate, and the accuracy of three-dimensional model processing is improved.

Optionally, according to the grid skeleton of the original grid model, obtaining the skeleton vertex corresponding to the target vertex, and determining the skeleton vertex as the height of the vertebral body corresponding to the original vertex, including: according to the grid framework of the original grid model, acquiring the space position coordinates of at least one vertex in the grid framework of the original grid model; acquiring space position coordinates of a target vertex; according to the space position coordinates corresponding to the target vertexes and the space position coordinates of at least one vertex in the grid framework of the original grid model, calculating the distances between the space position coordinates corresponding to the target vertexes and the space position coordinates of the vertexes in the grid framework of each original grid model; and acquiring the space position coordinates corresponding to the target vertexes and the vertexes with the minimum vertex distances in the grid framework of the original grid model, determining the vertexes as framework vertexes corresponding to the target vertexes, and determining the heights of vertexes corresponding to the original vertexes.

The spatial position coordinates may be coordinates of positions of vertices in a three-dimensional space.

Specifically, the grid skeleton of the original grid model comprises at least one skeleton vertex. For each target vertex, calculating the distance between the space position coordinates of the target vertex and the space position coordinates of each framework vertex on the grid framework, and selecting the framework vertex closest to the target vertex on the grid framework as the framework vertex corresponding to the target vertex. And determining the height of the vertebral body corresponding to the original vertex according to the skeleton vertex.

In one example, the original mesh model includes an original vertex 1, an original vertex 2, and an original vertex 3, and the original vertex 1 is taken as a target vertex. The grid framework of the original grid model comprises a framework vertex 1 and a framework vertex 2, and the distance between the space position coordinate corresponding to the target vertex and the space position coordinates of the framework vertex 1 and the framework vertex 2 is calculated according to the space position coordinate corresponding to the target vertex and the space position coordinates of the framework vertex 1 and the framework vertex 2; and acquiring the space position coordinate corresponding to the target vertex and the minimum distance from the framework vertex 1, and determining the framework vertex corresponding to the target vertex as the framework vertex 1, thereby determining the height of the cone corresponding to the original vertex.

The distance between the space position coordinates corresponding to the target vertexes and the space position coordinates of vertexes in the grid framework of each original grid model is calculated, the vertex with the minimum distance between the space position coordinates corresponding to the target vertexes and the vertexes in the grid framework of the original grid model is obtained, the vertex is determined to be the framework vertex corresponding to the target vertexes, the height of the cone corresponding to the original vertexes is determined, the framework vertexes can be corresponding to the target vertexes, and the problem that the target vertexes correspond to a plurality of framework vertexes is avoided.

Optionally, for each original vertex, adding the volume of the cone corresponding to the original vertex to the laplace energy equation corresponding to the original vertex to obtain an optimized laplace energy equation corresponding to the original vertex, including: obtaining an energy coefficient corresponding to an original vertex; and aiming at each original vertex, acquiring an optimized Laplace energy equation corresponding to the original vertex according to the volume of the vertebral body, the energy coefficient and the Laplace energy equation corresponding to the original vertex.

The energy coefficient corresponding to the original vertex can be a numerical factor of the volume of the vertebral body. The energy coefficient corresponding to the original vertex can be obtained through multiple tests.

Specifically, the volume of the vertebral body corresponding to the original vertex is as follows:

the standard Laplace energy equation is as follows:

E(v)＝||δ-Lv||²

Where L is the laplace operator, δ=lv= [ δ ₁ ^T,δ₂ ^T,...,δ_n ^T]^T is the laplace coordinate. The cone volume corresponding to the original vertex is introduced into a Laplace energy equation, and the optimized Laplace energy equation corresponding to the original vertex is obtained by aiming at the cone volume, the energy coefficient and the Laplace energy equation corresponding to the original vertex, wherein the optimized Laplace energy equation corresponding to the original vertex is shown as follows:

E(v)＝||δ-Lv||²-μV

Where V is the volume of the cone and μ is the energy coefficient corresponding to the original vertex.

In one example, the energy coefficient corresponding to the original vertex 1 is obtained, and the optimized laplace energy equation corresponding to the original vertex 1 is obtained by compensating the laplace energy equation through the vertebral volume corresponding to the original vertex 1 and the energy coefficient corresponding to the original vertex 1.

The method comprises the steps of obtaining energy coefficients corresponding to original vertexes, obtaining an optimized Laplace energy equation corresponding to the original vertexes according to the volumes of the vertexes, the energy coefficients and the Laplace energy equation corresponding to the original vertexes, performing cone volume compensation on the Laplace energy equation, and restricting the spatial positions of the original vertexes in the deformation process through the volumes so as to avoid the problem that the motion grid model generated by the original grid model in the deformation process is distorted.

Example two

Fig. 3 is a flowchart of a three-dimensional model processing method according to a second embodiment of the present invention. The embodiment of the invention optimizes and improves the three-dimensional model processing operation on the basis of the embodiment.

Further, screening at least one skeleton vertex from the original vertexes of the original grid model, determining that the skeleton vertex corresponding to each original vertex is thinned to the original vertex, and obtaining a Laplacian equation corresponding to the original vertex; acquiring a principal curvature corresponding to the original vertex according to the original vertex and the original edge of the original grid model; obtaining a tightening force constraint matrix and an attractive force constraint matrix corresponding to the original vertexes according to the original vertexes and the original edges of the original grid model and the principal curvatures corresponding to the original vertexes; calculating a shrinkage vertex corresponding to the original vertex according to the compaction force constraint matrix, the attraction force constraint matrix and the Laplace equation corresponding to the original vertex; obtaining a simplified grid model according to the contracted vertexes; extracting a grid framework of the original grid model according to the simplified grid model; and determining skeleton vertexes corresponding to the original vertexes according to vertexes on the grid skeleton of the original grid model so as to perfect the operation of processing the three-dimensional model.

In the embodiments of the present invention, the descriptions of other embodiments may be referred to in the portions not described in detail.

Referring to fig. 3, the three-dimensional model processing method includes:

s301, acquiring an original grid model of the three-dimensional object.

S302, acquiring a Laplace equation corresponding to each original vertex.

The laplace equation may be a method for calculating a spatial position during deformation of an original vertex.

Specifically, the spatial position coordinates of each original vertex are obtained. Substituting the space position coordinates of each original vertex into the Laplace equation to obtain the Laplace equation corresponding to each original vertex.

In one example, the spatial position coordinates of the original vertex 1 are obtained. And obtaining a Laplace equation through user input, substituting the space position coordinates of the original vertex 1 into the Laplace equation, and obtaining the Laplace equation corresponding to the original vertex 1.

S303, acquiring the principal curvature corresponding to the original vertex according to the original vertex and the original edge of the original grid model.

Wherein the principal curvature may be a numerical value describing the degree of curvature of the original vertices on the surface of the original mesh model.

Specifically, according to the original vertex of the original grid model and the curved surface where the original edge is located, one curve exists in an infinite number of orthogonal curvatures of the original vertex, wherein the curvature is the maximum value in all the curvatures, namely the main curvature corresponding to the original vertex.

Delta is the Laplace coordinate, and the calculation formula of delta is as follows:

δ＝LV＝[δ₁ ^T,δ₂ ^T,...,δ_n ^T]^T

δ_i＝-4A_iK_in_i

Where A _i is the base area corresponding to the original vertex, K _i the principal curvature, and n _i is the outer normal vector of the original vertex i.

In one example, according to the original vertex of the original mesh model and the curved surface where the original edge is located, the original vertex 1 has an infinite number of orthogonal curvatures, and the maximum value in all the curvatures is selected as the principal curvature corresponding to the original vertex 1.

S304, obtaining a tightening force constraint matrix and an attractive force constraint matrix corresponding to the original vertexes according to the original vertexes and the original edges of the original grid model and the principal curvatures corresponding to the original vertexes.

The compaction force constraint matrix may be a matrix that shrinks the original mesh model by a bottom area constraint of a corresponding vertebral body of the original vertex. The attractive force constraint matrix may be a matrix that contracts the original mesh model through principal curvature constraints corresponding to the original vertices.

Specifically, an original mesh model is input as follows for a given original mesh model:

G＝(V,E)

where V is the set of original vertices, E is the set of original edges, where,

V＝[V₁ ^T,V₂ ^T,...,V_n ^T]^T

T is the spatial position of the original vertex. Extracting a linear skeleton from the original grid model, namely extracting a grid skeleton, wherein the grid skeleton expression is as follows:

S＝(U,B)

u is the collection of skeleton vertexes, B is the collection of skeleton edges,

U＝[U₁ ^T,U₂ ^T,...,U_n ^T]^T

T is the set of skeleton vertex positions. The discrete Laplace equation is shown below:

LV'＝0

Where L is a laplace operator, which is an n×n matrix, and the calculation method of the matrix L is as follows:

Where α _ij and β _ij are two opposite angles to which the edges (i, j) correspond.

δ＝LV＝[δ₁ ^T,δ₂ ^T,...,δ_n ^T]^T

The above representation is a Laplace coordinate describing the relationship of the mesh vertices and their neighborhood vertices, the representation includes continuous and discrete forms,

δ_i＝-4A_iK_in_i

Wherein A _i,K_i and n _i are the base area corresponding to the original vertex, the principal curvature, the outer normal vector of the vertex i, and the original mesh model can be contracted by solving the Laplace equation.

Since the matrix L is a singular matrix, V 'cannot be directly found, and in order to find a unique solution for V', a constraint must be added to the matrix L. To avoid excessive shrinkage, so that the shrunken mesh better approximates the original mesh model, soft constraints, referred to herein as attractive force constraints and constrictive force constraints, are set.

The principal curvature measures how much a curved surface bends differently in different directions at a given point. In order to achieve the goal of different shrinkage in different areas of the model, for example, where the area resembles a flat plate, the degree of shrinkage is smaller, and where the other curvature is greater, the degree of shrinkage is greater, introducing principal curvature constraints. Introducing principal curvature constraint, namely adding the principal curvature constraint on the Laplace equation, and performing grid shrinkage, namely solving the following equation:

Where W _L is a compaction force matrix, W _H is an attractive force matrix with principal curvature constraints, solving the above equation by least squares, the equation variant being as follows, to minimize the value of the above equation,

In one example, according to the original vertex 1 and the original edge of the original mesh model and the principal curvature corresponding to the original vertex 1, the tightening force constraint matrix and the attraction force constraint matrix corresponding to the original vertex 1 are obtained through formulas corresponding to the tightening force constraint matrix and the attraction force constraint matrix.

S305, calculating the shrinkage vertexes corresponding to the original vertexes according to the shrinkage force constraint matrix, the attraction force constraint matrix and the Laplacian equation corresponding to the original vertexes.

The contracted vertex can be a vertex calculated by contraction of the original grid model.

Specifically, a new laplace operator L ^t+1 is calculated by using an original vertex position V ^t+1 through a laplace operator formula, and the shrinkage vertex V ^t+1 corresponding to the original vertex is calculated by iterative calculation according to a compaction force constraint matrix, an attraction force constraint matrix and a laplace equation corresponding to the original vertex. The iterative process of mesh contraction that introduces principal curvature constraints becomes the following steps: the following equation is solved:

solving a vertex set V ^t+1; updating the value of W _L to W _L ^t+1＝S_LW_L ^t,W_H,i is updated to the following:

Wherein the method comprises the steps of Where k ₁ and k ₂ are the principal curvatures of the model vertices and A _i ^t and A _i ⁰ are the base areas of the current original vertex corresponding to the neighborhood vertices of the original vertex, respectively.

In one example, the shrinkage vertex corresponding to the original vertex is iteratively calculated according to the compaction force constraint matrix, the attraction force constraint matrix and the Laplace equation corresponding to the original vertex, and the final simplified and completed shrinkage vertex corresponding to the original grid model is obtained.

S306, acquiring a simplified grid model according to the contracted vertexes.

The simplified grid model may be a grid model generated by performing shrinkage calculation on an original grid model.

Specifically, according to the connection relation between the shrinkage vertexes and the shrinkage vertexes, a simplified grid model corresponding to the original grid model is generated. The reduced mesh model after contraction is a two-dimensional model with the vertex set as follows:

V＝[V₁ ^T,V₂ ^T,...,V_n ^T]^T

the reduced mesh model after contraction appears visually as a one-dimensional skeleton, which essentially still has connectivity of the original mesh model, and so is still two-dimensional.

In one example, as shown in FIG. 4, α represents the number of iterations as a result of the original mesh model after 8 iterations. After each iteration, the contraction weight corresponding to the contraction force matrix and the attraction weight corresponding to the attraction matrix of each original vertex are updated. As can be seen from the results, in the first four iterations, the shrinkage effect is not obvious because the shrinkage weight and the gravitational weight are not changed much, and in the fifth and later iterations, because the weight is changed much, the larger the constraint on the original mesh model is, the more obvious the shrinkage effect is, and even by the eighth iteration, the whole original mesh model visually looks like a one-dimensional linear skeleton. And it can be seen that for the areas of the model flat plate portions, the degree of shrinkage is smaller, while other portions of greater curvature, the degree of shrinkage is greater.

S307, extracting a grid framework of the original grid model according to the simplified grid model.

In particular, the simplified mesh model is still two-dimensional in nature, in that it still has connectivity of the original mesh model, and a join operation is required to convert the two-dimensional mesh model into a one-dimensional skeleton. The process of the join operation is a series of edge cancellations in order to remove patches from the contracted mesh until all patches are removed, and it is most important to maintain the shape of the degenerate mesh, i.e., to maintain sufficient number of skeleton vertices to maintain the consistency of the mesh skeleton and the original mesh model, during the join operation. By setting the cost function, the cost function comprises a shape cost function and a sampling cost function, the connection operation adopts a greedy algorithm, and the edge with the minimum cost is selected to be eliminated in each iteration process. The data structure adopts a half-structure, such as merging point i to point j for half i→j, and removing all patches adjacent to half i→j, which does not break a connected grid. In order to preserve the topology of the mesh, if k is the common contiguous edge of i and j and there are half edges i→j, j→k, k→i, i.e. three half edges form a ring, in which case the edges i→j are not eliminated, such constraint ensures that the one-dimensional skeleton has the same number of cycles (half cycles) as the original mesh model.

The method of shape cost function is similar to QEM grid simplification, the geometric characteristics of the grid can be well maintained, and QEM estimates distortion (distortion) caused by elimination of one edge by calculating an error matrix of each vertex by calculating the square sum of distances from the vertex to all adjacent patches. This method of calculating the patch-based error is not applicable here because the patches of the mesh after shrinking have an area of zero. An edge-based approach like QEM is employed here. Specifically, first, for each side i→j of the reduced mesh model, a matrix K _ij is defined, which is the square of the distance from the vertex p to the side i→j, as shown in the following formula:

Where a is the normal vector for side (i, j), b=a×v _i, and the error matrix for the initial vertex i represents the sum of squares of the distances of the neighbor vertex p to all sides adjacent to i, as shown in the following equation:

In the simplified process, in order to keep the shape of the original grid model as much as possible, selecting one edge with the minimum cost for elimination, and the cost calculation method is as follows:

The next edge to be eliminated (i, j) is the edge where the sum of squares of the distances of the points V _j to all edges adjacent to i and j is the smallest (if the previous point is eliminated and attributed to point i or point j, then the distances of V _j to all edges adjacent to these points are also the smallest), and after one edge elimination, the error matrix of vertex j is updated to Q _j＝Q_i+Q_j so that the edges previously adjacent to vertex i are all instead adjacent to vertex j. Wherein the error matrix is a matrix of 4*4.

The shape cost function can well maintain the shape of the original grid, however, in some areas, excessive simplification, such as a curved arc, is generated, and the shape cost function is simplified into a straight line, so that the topological shape of the original grid is lost, and good consistency between the skeleton and the original grid model cannot be maintained. The sampling cost function is to avoid this, as follows:

the sampling cost function represents the distance from vertex i to vertex j multiplied by the sum of the distances of all vertices (denoted by k) to which vertex i adjoins.

The total cost is the sum of the shape cost and the sampling cost, as follows:

Here ω _a＝1.0,ω_b =0.1, the shape cost increases during the iteration because the error matrix accumulates as the iteration proceeds. The increase in shape cost mainly controls the elimination of edges, maintaining the shape of the original contracted grid, resulting in a grid skeleton, as shown in fig. 5.

S308, determining skeleton vertexes corresponding to the original vertexes according to vertexes on the grid skeleton of the original grid model.

Specifically, according to the distance between each original vertex and each skeleton vertex on the grid skeleton, selecting the skeleton vertex with the smallest distance as the skeleton vertex corresponding to the original vertex.

In one example, distances between the original vertex 1 and the skeleton vertex 1 and between the original vertex 1 and the skeleton vertex 2 on the grid skeleton are calculated respectively, the distance between the original vertex 1 and the skeleton vertex 1 on the grid skeleton is smaller than the distance between the original vertex 1 and the skeleton vertex 2 on the grid skeleton, and the skeleton vertex 1 is selected as the skeleton vertex corresponding to the original vertex 1.

S309, for each original vertex, calculating the volume of the vertebral body corresponding to the original vertex according to the original vertex and the skeleton vertex corresponding to the original vertex.

S310, aiming at each original vertex, acquiring a Laplace energy equation corresponding to the original vertex.

And S311, adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex aiming at each original vertex to obtain the optimized Laplace energy equation corresponding to the original vertex.

S312, obtaining a motion grid model of the three-dimensional object according to the optimized Laplace energy equation corresponding to each original vertex.

According to the embodiment of the invention, the principal curvatures corresponding to the original vertexes are obtained through the original vertexes and the original edges of the original grid model, the tightening force constraint matrix and the attraction constraint matrix corresponding to the original vertexes are obtained, the shrinkage vertexes corresponding to the original vertexes are calculated, the simplified grid model is obtained, the grid skeleton of the original grid model is extracted, the skeleton vertexes corresponding to the original vertexes are determined, the corresponding relations between the original vertexes and the skeleton vertexes can be obtained, the cone volume corresponding to the original vertexes is calculated, and the distortion generated in the processing process of the three-dimensional model is reduced through cone volume constraint.

Optionally, according to the optimized laplace energy equation corresponding to each original vertex, a motion grid model of the three-dimensional object is obtained, including: obtaining an optimized Laplace energy equation corresponding to the original vertex according to the original vertex of the original grid model; obtaining an optimized Laplace coordinate corresponding to the original vertex according to the optimized Laplace energy equation; generating a motion grid model edge according to the optimized Laplace coordinates corresponding to the original vertexes; and generating a motion grid model of the three-dimensional object according to the optimized Laplace coordinates corresponding to the original vertexes and the motion grid model edges.

The optimized laplace coordinate may be a laplace coordinate calculated through an optimized laplace energy equation. The motion mesh model edge may be an edge connecting vertices at the optimized laplace coordinates.

Specifically, according to the original vertexes of the original grid model, an optimized Laplace energy equation corresponding to the original vertexes is obtained, optimized Laplace coordinates corresponding to the original vertexes are obtained through calculation according to the optimized Laplace energy equation, a motion grid model edge is generated according to the optimized Laplace coordinates corresponding to the original vertexes, a motion grid model corresponding to the original grid model of the three-dimensional object is generated according to the optimized Laplace coordinates corresponding to the original vertexes and the motion grid model edge, and distortion generated in the motion process of the original grid model can be reduced.

In one example, as shown in fig. 6, the spatial position coordinates of the original vertices of the original mesh model are substituted into an optimized laplace energy equation, so as to obtain optimized laplace coordinates corresponding to the original vertices, a motion mesh model edge is generated according to the optimized laplace coordinates corresponding to the original vertices, and a motion mesh model of the three-dimensional object is generated according to the optimized laplace coordinates corresponding to the original vertices and the motion mesh model edge.

And generating a motion grid model of the three-dimensional object according to the optimized Laplace coordinates and the motion grid model edges corresponding to the original vertexes by acquiring the optimized Laplace energy equation corresponding to the original vertexes, reducing distortion generated in the motion process of the original grid model, and improving the accuracy of the three-dimensional model processing.

Optionally, the three-dimensional object comprises: virtual digital person.

Wherein, the virtual digital person can be a digital character image which is created by digital technology and is close to the human image.

In particular, the virtual digital person can be applied to the field of banks. The bank virtual digital person is more complex from algorithm to design, to engineering and integration, integrates multiple artificial intelligence technologies such as vision, semanteme, voice and the like, can simulate the form, expression and action of a human body, creates a highly anthropomorphic virtual image, and has hearing and speaking capabilities. That is, the bank virtual digital person is provided with the whole artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) capability of voice recognition (Automated Speech Recognition, ASR), natural language understanding (Nature Language Processing, NLP), voice synthesis (Text To Speech, TTS) and image driven technology (IMAGE DRIVEN technology, IDT) at the same time. The Image Driving Technology (IDT) is one of intelligent graphic technologies, and combines a deep learning neural network and computer graphics to enable a computer to understand the content of voice and finely drive the lip movements, facial expressions and limb gestures of an avatar, thereby endowing the avatar with a real and intimate avatar to a digital person.

In one example, the original mesh model of the three-dimensional object may be an original mesh model of a virtual digital person in the banking domain. The original grid model of the virtual digital person in the banking field is shown in fig. 7, and the image of the virtual digital person is shown in fig. 8 by rendering the model with specific materials and lights.

The three-dimensional object can be a virtual digital person, so that distortion of a grid model of the virtual digital person in a motion process can be reduced, and the accuracy of processing the three-dimensional model is improved.

Example III

Fig. 9 is a schematic structural diagram of a three-dimensional model processing device according to a third embodiment of the present invention. The embodiment of the invention is applicable to the situation of three-dimensional model processing, the device can execute a three-dimensional model processing method, and the device can be realized in a form of hardware and/or software.

Referring to fig. 9, the three-dimensional model processing apparatus includes: a model acquisition module 901, a vertex determination module 902, a volume calculation module 903, an equation acquisition module 904, an optimization equation acquisition module 905, and a motion model acquisition module 906, wherein,

The model acquisition module 901 is used for acquiring an original grid model of the three-dimensional object;

The vertex determining module 902 is configured to screen at least one skeleton vertex from the original vertices of the original mesh model, and determine skeleton vertices corresponding to the original vertices;

The volume calculation module 903 is configured to calculate, for each original vertex, a volume of a vertebral body corresponding to the original vertex according to the original vertex and a skeleton vertex corresponding to the original vertex;

The equation obtaining module 904 is configured to obtain, for each original vertex, a laplace energy equation corresponding to the original vertex;

the optimization equation obtaining module 905 is configured to, for each original vertex, add a volume of a cone corresponding to the original vertex to a laplace energy equation corresponding to the original vertex, and obtain an optimized laplace energy equation corresponding to the original vertex;

the motion model obtaining module 906 is configured to obtain a motion grid model of the three-dimensional object according to the optimized laplace energy equation corresponding to each original vertex.

According to the technical scheme, the vertebral body volume corresponding to the original vertex is calculated through the original vertex and the skeleton vertex corresponding to the original vertex, the Laplace energy equation corresponding to the original vertex is obtained, the vertebral body volume corresponding to the original vertex is added into the Laplace energy equation corresponding to the original vertex, the optimized Laplace energy equation corresponding to the original vertex is obtained, the motion grid model of the three-dimensional object is obtained according to the optimized Laplace energy equation corresponding to each original vertex, the motion grid model of the three-dimensional object is obtained through the vertebral body volume compensation Laplace energy equation, distortion generated in the motion process of the original grid model of the three-dimensional object is reduced, and the accuracy of three-dimensional model processing can be improved.

Optionally, the vertex determining module 902 is specifically configured to:

aiming at each original vertex, acquiring a Laplace equation corresponding to the original vertex;

Acquiring a principal curvature corresponding to the original vertex according to the original vertex and the original edge of the original grid model;

Obtaining a tightening force constraint matrix and an attractive force constraint matrix corresponding to the original vertexes according to the original vertexes and the original edges of the original grid model and the principal curvatures corresponding to the original vertexes;

Calculating a shrinkage vertex corresponding to the original vertex according to the compaction force constraint matrix, the attraction force constraint matrix and the Laplace equation corresponding to the original vertex;

Obtaining a simplified grid model according to the contracted vertexes;

Extracting a grid framework of the original grid model according to the simplified grid model;

and determining skeleton vertexes corresponding to the original vertexes according to vertexes on the grid skeleton of the original grid model.

Optionally, the volume calculation module 903 includes:

A target vertex selecting unit for selecting a target vertex according to the original vertex of the original grid model;

the neighborhood vertex determining unit is used for determining a neighborhood vertex corresponding to the target vertex according to the original edge of the original grid model and the target vertex;

the bottom area determining unit is used for determining the bottom area of the cone corresponding to the original vertex according to the original side of the original grid model, the target vertex and the domain vertex corresponding to the target vertex;

the numerical value determining unit is used for obtaining skeleton vertexes corresponding to the target vertexes according to the grid skeleton of the original grid model and determining heights of vertebral bodies corresponding to the original vertexes;

the volume acquisition unit is used for acquiring the volume of the vertebral body corresponding to the target vertex according to the volume and height of the bottom surface of the vertebral body corresponding to the original vertex.

Optionally, the optimization equation acquisition module 905 is specifically configured to:

obtaining an energy coefficient corresponding to an original vertex;

And aiming at each original vertex, obtaining an optimized Laplace energy equation corresponding to the original vertex by using the cone volume, the energy coefficient and the Laplace energy equation corresponding to the original vertex.

Optionally, the motion model obtaining module 906 is specifically configured to:

Obtaining an optimized Laplace energy equation corresponding to the original vertex according to the original vertex of the original grid model;

obtaining an optimized Laplace coordinate corresponding to the original vertex according to the optimized Laplace energy equation;

Generating a motion grid model edge according to the optimized Laplace coordinates corresponding to the original vertexes;

and generating a motion grid model of the three-dimensional object according to the optimized Laplace coordinates corresponding to the original vertexes and the motion grid model edges.

Optionally, the three-dimensional object comprises: virtual digital person.

Optionally, the numerical value determining unit is specifically configured to:

According to the grid framework of the original grid model, acquiring the space position coordinates of at least one vertex in the grid framework of the original grid model;

Acquiring space position coordinates of a target vertex;

According to the space position coordinates corresponding to the target vertexes and the space position coordinates of at least one vertex in the grid framework of the original grid model, calculating the distances between the space position coordinates corresponding to the target vertexes and the space position coordinates of the vertexes in the grid framework of each original grid model;

and acquiring the space position coordinates corresponding to the target vertexes and the vertexes with the minimum vertex distance in the grid framework of the original grid model, determining the vertexes as framework vertexes corresponding to the target vertexes, and determining the vertexes as the heights of vertexes corresponding to the original vertexes.

The three-dimensional model processing device provided by the embodiment of the invention can execute the three-dimensional model processing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the three-dimensional model processing method.

Example IV

Fig. 10 shows a schematic diagram of a three-dimensional model processing apparatus 1000 that may be used to implement an embodiment of the invention.

As shown in fig. 10, the three-dimensional model processing device 1000 includes at least one processor 1001, and a memory such as a Read Only Memory (ROM) 1002, a Random Access Memory (RAM) 1003, etc. communicatively connected to the at least one processor 1001, wherein the memory stores a computer program executable by the at least one processor, and the processor 1001 can perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 1002 or the computer program loaded from the storage unit 1008 into the Random Access Memory (RAM) 1003. In the RAM1003, various programs and data required for the operation of the three-dimensional model processing apparatus 1000 can also be stored. The processor 1001, the ROM1002, and the RAM1003 are connected to each other by a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.

A plurality of components in the three-dimensional model processing apparatus 1000 are connected to the I/O interface 1005, including: an input unit 1006 such as a keyboard, a mouse, and the like; an output unit 1007 such as various types of displays, speakers, and the like; a storage unit 1008 such as a magnetic disk, an optical disk, or the like; and communication unit 1009 such as a network card, modem, wireless communication transceiver, etc. Communication unit 1009 allows three-dimensional model processing device 1000 to exchange information/data with other devices via a computer grid, such as the internet, and/or various telecommunications grids.

The processor 1001 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of processor 1001 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 1001 performs the respective methods and processes described above, for example, a three-dimensional model processing method.

In some embodiments, the three-dimensional model processing method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 1008. In some embodiments, part or all of the computer program may be loaded and/or installed onto the three-dimensional model processing device 1000 via the ROM1002 and/or the communication unit 1009. When the computer program is loaded into RAM1003 and executed by processor 1001, one or more steps of the three-dimensional model processing method described above may be performed. Alternatively, in other embodiments, the processor 1001 may be configured to perform the three-dimensional model processing method in any other suitable manner (e.g., by means of firmware).

Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a three-dimensional model processing device, the vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or a trackball) through which a user can provide input to the three-dimensional model processing device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a grid browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication grid). Examples of communication grids include: local Area Networks (LANs), wide Area Networks (WANs), blockchain grids, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communications grid. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and Virtual private server (VPS PRIVATE SERVER) service.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims

1. A method of three-dimensional model processing, the method comprising:

acquiring an original grid model of a three-dimensional object;

For each original vertex, acquiring a Laplace energy equation corresponding to the original vertex;

for each original vertex, adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex to obtain an optimized Laplace energy equation corresponding to the original vertex;

2. The method of claim 1, wherein screening at least one skeleton vertex among the original vertices of the original mesh model and determining a skeleton vertex corresponding to each of the original vertices comprises:

for each original vertex, acquiring a Laplace equation corresponding to the original vertex;

Acquiring a principal curvature corresponding to an original vertex according to the original vertex and an original edge of the original grid model;

calculating a shrinkage vertex corresponding to the original vertex according to a compaction force constraint matrix, an attraction force constraint matrix and the Laplace equation corresponding to the original vertex;

obtaining a simplified grid model according to the contracted vertexes;

3. The method of claim 1, wherein for each of the original vertices, calculating a volume of a vertebral body corresponding to the original vertex from the original vertex and a skeleton vertex corresponding to the original vertex, comprising:

Selecting a target vertex according to the original vertex of the original grid model;

Determining a domain vertex corresponding to the target vertex according to the original edge of the original grid model and the target vertex;

determining the bottom area of a cone corresponding to the original vertex according to the original edge of the original grid model, the target vertex and the neighborhood vertex corresponding to the target vertex;

Obtaining skeleton vertexes corresponding to the target vertexes according to the grid skeleton of the original grid model, and determining heights of vertebral bodies corresponding to the original vertexes;

and acquiring the volume of the vertebral body corresponding to the target vertex according to the volume and height of the bottom surface of the vertebral body corresponding to the original vertex.

4. The method of claim 1, wherein for each of the original vertices, adding the volume of the vertebral body corresponding to the original vertex to the laplace energy equation corresponding to the original vertex to obtain the optimized laplace energy equation corresponding to the original vertex, comprising:

acquiring an energy coefficient corresponding to the original vertex;

And for each original vertex, according to the volume of the vertebral body corresponding to the original vertex, the energy coefficient and the optimized Laplace energy equation corresponding to the original vertex, wherein the energy coefficient and the Laplace energy equation Cheng Huoqu are used for optimizing the Laplace energy equation.

5. The method of claim 1, wherein obtaining the motion grid model of the three-dimensional object from the optimized laplace energy equation corresponding to each of the original vertices comprises:

6. The method of claim 1, wherein the three-dimensional object comprises: virtual digital person.

7. The method of claim 3, wherein obtaining the skeleton vertex corresponding to the target vertex from the mesh skeleton of the original mesh model, determining the height of the vertebral body corresponding to the original vertex, comprises:

Acquiring the space position coordinates of at least one vertex in the grid framework of the original grid model according to the grid framework of the original grid model;

acquiring the space position coordinates of the target vertexes;

calculating the distance between the spatial position coordinate corresponding to the target vertex and the spatial position coordinate of the vertex in the grid framework of each original grid model according to the spatial position coordinate corresponding to the target vertex and the spatial position coordinate of at least one vertex in the grid framework of the original grid model;

And acquiring the space position coordinates corresponding to the target vertexes and the vertexes with the minimum vertex distance in the grid framework of the original grid model, determining the vertexes as framework vertexes corresponding to the target vertexes, and determining the heights of vertexes corresponding to the original vertexes.

8. A three-dimensional model processing apparatus, the apparatus comprising:

the optimization equation acquisition module is used for adding the cone volume corresponding to the original vertex into the Laplace energy equation corresponding to the original vertex to obtain an optimized Laplace energy equation corresponding to the original vertex;

9. A three-dimensional model processing apparatus, characterized in that the three-dimensional model processing apparatus comprises:

At least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the three-dimensional model processing method of any one of claims 1-7.

10. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to implement the three-dimensional model processing method according to any one of claims 1-7 when executed.