CN111275805B - Model mesh optimization method and device based on 3D model texture - Google Patents
Model mesh optimization method and device based on 3D model texture Download PDFInfo
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- CN111275805B CN111275805B CN202010065266.XA CN202010065266A CN111275805B CN 111275805 B CN111275805 B CN 111275805B CN 202010065266 A CN202010065266 A CN 202010065266A CN 111275805 B CN111275805 B CN 111275805B
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Abstract
The application discloses a model mesh optimization method and device based on 3D model textures, which utilize energy loss indexes and texture seam loss indexes of edge-shrunk geometric features to constrain edge shrinkage conditions of furniture models, can quickly and effectively simplify the furniture models and keep the geometric features and the texture features of the furniture models, simultaneously avoid serious texture distortion caused by model simplification, is not limited by texture parameterization continuity, and solves the technical problems that obvious texture distortion of the furniture models easily occurs in the conventional simplification mode of parameterization requiring textures due to the fact that the furniture models usually have rich texture information, and reliability is lower.
Description
Technical Field
The application relates to the technical field of 3D model processing, in particular to a model mesh optimization method and device based on 3D model textures.
Background
The digital furniture model design provides a convenient and direct model interaction way for people, so that users can obtain furniture visual sense without checking physical furniture on site.
In order to visualize a furniture model, designers typically use design software to create a three-dimensional furniture geometric design and define appropriate textures for the different parts, and then generate furniture rendering results using a rendering tool. Generally, a furniture supplier maintains a huge database of furniture models, each of which has a large initial design with abundant geometric details, and a detailed furniture model can provide users with abundant details and good reality, but the more details a furniture model contains, the more time is required for loading and rendering data, and therefore, there is a great need to simplify the furniture model while maintaining the complete appearance and overall texture of the furniture.
The existing method for simplifying the furniture model is to expand a three-dimensional vector representing a space coordinate and introduce RGB three components representing colors to combine into a 6-dimensional vector, so that each vertex of a three-dimensional grid is represented as a point of a six-dimensional space, and secondary error optimization is performed in the six-dimensional space to achieve the minimum loss of a visual effect. Therefore, it is an urgent technical problem to be solved by those skilled in the art to provide a furniture model simplification method which can simplify a model while maintaining the 3D model texture of furniture and avoid the problem of apparent furniture model texture distortion.
Disclosure of Invention
The application provides a model mesh optimization method and device based on 3D model textures, which are used for solving the technical problems that obvious furniture model texture distortion easily occurs and the reliability is low in the conventional simplified mode of texture parameterization required because furniture models usually have abundant texture information.
In view of the above, a first aspect of the present application provides a model mesh optimization method based on 3D model texture, including:
reading a target furniture model, and acquiring grid model information and texture information of the target furniture model;
performing grid simplification on the target furniture model according to a target simplification rate and an edge simplification priority input by a user to obtain a simplified first furniture model, wherein the grid simplification is constrained by an edge contraction constraint condition, and the edge contraction constraint condition is as follows:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, and ε is a threshold.
Optionally, the mesh simplification is performed on the target furniture model according to the target simplification rate and the edge simplification priority input by the user to obtain a simplified first furniture model, and then the method further includes:
and detecting whether a new target simplification rate is received, if so, restoring the simplified first furniture model into the target furniture model, and then carrying out grid simplification on the target furniture model according to the new target simplification rate and the edge simplification priority to obtain a simplified second furniture model.
Optionally, after the target furniture model is read and the mesh model information and the texture information of the target furniture model are obtained, mesh simplification is performed on the target furniture model according to a target simplification rate and an edge simplification priority input by a user to obtain a simplified first furniture model, and the method further includes:
determining edge merging vertexes based on the energy loss of the minimum edge geometric characteristics according to the mesh model information to obtain a contracted edge;
calculating texture seam loss and symmetric texture factors of the contraction edge;
calculating the energy of each edge according to the geometric characteristic energy loss of the contraction edge, the texture seam loss and the symmetrical texture factor, wherein the energy calculation formula is as follows:
Eedge＝λEshape+(1+λ)Eseam+δ
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeFor edge geometry characteristic energy losses, EseamFor texture seam loss, δ is the symmetric texture factor;
edge reduction priorities are determined from the energy of each edge, with lower energy edges having higher pinch priorities.
Optionally, the calculation formula of the edge geometric characteristic energy loss is as follows:
where w (-) is a weight function of a monotonically increasing function with respect to the triangle area S, df(v) Point-to-face distance, N, from vertex v to face fF(v) All adjacent surfaces of the vertex v, each edge passing through a minimum EshapeCan be used forObtaining the optimal edge merging vertex vnew。
Optionally, the texture seam loss of the shrink side is calculated by the following formula:
wherein v is0And v1Is a seam edge v0v1T is transposed.
Optionally, the symmetric texture factor is:
where Ω is the set of edges.
Optionally, the grid simplifying the target furniture model according to the target simplification rate and the edge simplification priority input by the user to obtain a simplified first furniture model, further including:
recording texture coordinates corresponding to the vertexes of the contracted edges, so that after the simplified first furniture model is restored to the target furniture model, the texture of the target furniture model is restored according to the texture coordinates
The second aspect of the present application provides a model mesh optimization device based on 3D model texture, comprising:
the reading module is used for reading a target furniture model and acquiring grid model information and texture information of the target furniture model;
a simplification module, configured to perform mesh simplification on the target furniture model according to a target simplification rate and an edge simplification priority input by a user, to obtain a simplified first furniture model, where the mesh simplification is constrained by an edge contraction constraint condition, where the edge contraction constraint condition is:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, and ε is a threshold.
Optionally, the method further comprises: a detection module;
the detection module is used for detecting whether a new target simplification rate is received or not, if yes, the simplified first furniture model is restored to the target furniture model, and then grid simplification is carried out on the target furniture model according to the new target simplification rate and the edge simplification priority, so that a simplified second furniture model is obtained.
Optionally, an edge energy calculation module is further included;
the edge energy calculation module is configured to:
determining edge merging vertexes based on the energy loss of the minimum edge geometric characteristics according to the mesh model information to obtain a contracted edge;
calculating texture seam loss and symmetric texture factors of the contraction edge;
calculating the energy of each edge according to the geometric characteristic energy loss of the contraction edge, the texture seam loss and the symmetrical texture factor, wherein the energy calculation formula is as follows:
Eedge＝λEshape+(1+λ)Eseam+δ
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeFor edge geometry characteristic energy losses, EseamFor texture seam loss, δ is the symmetric texture factor;
edge reduction priorities are determined from the energy of each edge, with lower energy edges having higher pinch priorities.
According to the technical scheme, the embodiment of the application has the following advantages:
the application provides a model mesh optimization method based on 3D model texture, which comprises the following steps: reading a target furniture model, and acquiring grid model information and texture information of the target furniture model; carrying out grid simplification on the target furniture model according to the target simplification rate and the edge simplification priority input by the user to obtain a simplified first furniture model, wherein the grid simplification is constrained by an edge contraction constraint condition, and the edge contraction constraint condition is as follows:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, and ε is a threshold. According to the model mesh optimization method based on the 3D model texture, the edge shrinkage condition of the furniture model is constrained by the energy loss index and the texture seam loss index of the edge shrinkage geometric feature, the furniture model can be quickly and effectively simplified, the geometric feature and the texture feature of the furniture model are kept, meanwhile, serious texture distortion caused by model simplification is avoided, the limitation of texture parameterization continuity is avoided, and the technical problems that obvious furniture model texture distortion easily occurs in the conventional simplification mode requiring texture parameterization due to the fact that the furniture model usually has rich texture information, and reliability is low are solved.
Drawings
Fig. 1 is a schematic flowchart of a model mesh optimization method based on 3D model texture provided in an embodiment of the present application;
fig. 2 is another schematic flow chart of a model mesh optimization method based on 3D model texture provided in an embodiment of the present application;
FIG. 3 is a diagram illustrating merging of two points into a new point during mesh reduction;
FIG. 4 is a schematic illustration of a seam of two different texture images;
FIG. 5 is a schematic diagram of a symmetric furniture mesh model;
FIG. 6 is a diagram illustrating a conventional progressive mesh reduction recovery method;
FIG. 7 is a schematic diagram illustrating the effect of different degrees of simplification;
fig. 8 is a schematic structural diagram of a model mesh optimization apparatus based on 3D model texture provided in an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
For ease of understanding, referring to fig. 1, the present application provides an embodiment of a model mesh optimization method based on 3D model texture, comprising:
102, carrying out grid simplification on a target furniture model according to a target simplification rate and a side simplification priority input by a user to obtain a simplified first furniture model, wherein the grid simplification is constrained by a side contraction constraint condition, and the side contraction constraint condition is as follows:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, and ε is a threshold.
It should be noted that, in the embodiment of the present application, first, a target furniture model input by a user needs to be read, so as to obtain mesh model information and texture information of the target furniture model. After the mesh model information is obtained, the energy of each edge can be determined, the priority of edge contraction is determined according to the energy of the edge, and edges with lower energy have higher contraction priority, namely, simplified priority. In order to realize the flexibility of the model simplification degree and provide more simplification effect choices for a user, in the embodiment of the application, a simplification rate input item is set, the user can select the simplification rate required to be simplified according to the needs, after the user inputs the simplification rate, software contracts and simplifies the edges of the grid furniture model according to the edge simplification priority, but in order to avoid deformity caused by too serious energy loss when the grid furniture model is simplified, in the embodiment of the application, the grid simplification limited condition is set to contract and restrict the edges of the grid furniture model, and e is setjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for all Eshape(ej) Maximum value of (1), Eseam(ej) Is ejThe texture seam loss of (1) is that alpha is a preset weight coefficient and can be set according to actual conditions, and epsilon is a threshold value and can be set according to the actual conditions, so that only the set is satisfied
Can be shrunk.
According to the model mesh optimization method based on the 3D model texture, the edge shrinkage condition of the furniture model is constrained by the energy loss index and the texture seam loss index of the edge shrinkage geometric feature, the furniture model can be quickly and effectively simplified, the geometric feature and the texture feature of the furniture model are kept, meanwhile, serious texture distortion caused by model simplification is avoided, the limitation of texture parameterization continuity is avoided, and the technical problems that the existing furniture model generally has rich texture information, the obvious texture distortion of the furniture model easily occurs in a parameterization simplification mode requiring the texture, and the reliability is low are solved.
For ease of understanding, referring to fig. 2, another embodiment of a model mesh optimization method based on 3D model texture is provided herein, comprising:
Eedge＝λEshape+(1+λ)Eseam+δ
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeFor edge geometry characteristic energy losses, EseamFor texture seam loss, δ is the symmetric texture factor.
It should be noted that the simplification of the grid is accomplished by merging two points to form a new point, as shown in FIG. 3, when (v) is paired1,v2) Generating new vertex v when the represented edge applies the edge shrink operationnewTo replace v1And v2. The replacement of two points by one point causes a visual loss, defined as w (-) as a weight function of a monotonically increasing function of the area S of the triangle, due to the triangular faces that make up the furniture modelThe sizes are different, and the large triangular surface has a larger influence on the overall geometric characteristics, so that a weight function needs to be added. df(v) For a point-to-face distance of a vertex v to an f-face, the loss of geometric features can be measured by the following equation:
wherein N isF(v) All the adjacent faces of the apex v are indicated. By minimizing EshapeV is availablenewSo that geometric losses are minimized. v. ofnewIs located by the distance v from the original grid surfacenewThe texture coordinate of the nearest point is assigned.
A seam is the area where two different texture images intersect as shown in fig. 4. The vertices on the seam contain multiple texture coordinates from different texture images. Simplifying these regions, if shown in fig. 4, can cause severe distortion of the texture.
For proper seam handling, the rule defining edge shrink is: for joint margin (v)1,v2) While the shrink operation makes it degenerate into v1Or v2. It is clear that shrinking at a small angle on the two joined seam edges does not lead to large deformations (no distortion if the seam is a straight line). More specifically, for seamed edges (v)0,v1) And (v)0,v2) Pair (v)0,v1) Is made v by the contracting operation1The loss was measured using the following criteria:
for edge shrinkage not belonging to the seam, EseamThe value is 0.
The furniture model is often a mesh model with symmetry, as shown in fig. 5, with vertices v0And v1Has the same texture coordinate when (v)0,v1) From v0Shrink to v1It will generate a triangleA patch, with the same texture coordinates at its different vertices, results in a large texture stretch. In the embodiment of the present application, to ensure that the symmetric texture is not destroyed during simplification, a symmetric texture factor item is introduced, where Ω is set as a set of edges, adjacent points of two vertices (two endpoints of an edge) of the set edge have vertices with the same texture coordinate, and δ is defined as (v) of the edge0,v1) Symmetric texture factors, there are:
in the embodiment of the application, the shrinkage of the edge is restrained by simultaneously considering the loss of the geometric features, the seam distortion factor and the symmetric texture factor. The contraction simplification priority of the edge is determined according to the energy of the edge, and the energy calculation mode of the edge is defined as follows:
Eedge＝λEshape+(1+λ)Eseam+δ；
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeFor edge geometry characteristic energy losses, EseamFor texture seam loss, δ is the symmetric texture factor.
Simply put, it is by minimizing E for each edgeshapeTo determine vnew，EseamIs also determined accordingly, and the reduced priority of the edge is given by EedgeDetermination of EedgeLower edges will be given higher priority, while edges of infinite energy will be forbidden to merge, EedgeThe smaller the edge, the higher the shrink priority of the edge, and update v accordinglynewSpatial coordinates and texture coordinates.
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, and ε is a threshold.
It should be noted that step 206 in the present embodiment is the same as step 102 in the previous embodiment, and is not described herein again.
And step 207, detecting whether a new target simplification rate is received, if so, restoring the simplified first furniture model into a target furniture model, and then carrying out grid simplification on the target furniture model according to the new target simplification rate and the edge simplification priority to obtain a simplified second furniture model.
It should be noted that in the actual furniture model simplification application scenario, the simplification result obtained after the user inputs the simplification rate may not be the result satisfied by the user, and the user may change the simplification rate to obtain another simplification result again. Therefore, the software needs to detect whether the user inputs a new simplification rate, if so, the software firstly restores the model of the simplification result of the user before inputting the new simplification rate, and then performs grid simplification on the target furniture model according to the new target simplification rate and the edge simplification priority to obtain the simplification result corresponding to the new target simplification rate. However, regarding the restoration method after mesh model simplification, the existing method is the progressive mesh simplification restoration proposed by Hoppe: when facing side (v) as shown in FIG. 60,v1) While performing the edge shrink operation, record v0And v1And record the edge (v)0,v1) Left and right (v)0→v1Direction determination left and right) two triangular faceslAnd vrAnd (v)0,v1) Is contracted to replace the point vnewThe primary side of the complex (v)0,v1) When it is, v willnewSplitting into v0And v1Then according to vlAnd vrRecovery of correctness v0And v1And restoring the topological structure through the connection relation with the surrounding points. According to research, the recovery result of the method is not always ideal, the recovery is malformed, and during the analysis of the malformation, the method is found to have no texture coordinate operation of the recorded points, so that ambiguity is easily generated in the recovery process, and the malformed result is recovered. In order to solve the problem of recovering deformity, the embodiment of the application records v based on the method0And v1After recovering the geometric topological structure, the recorded texture coordinate is given to v0And v1And recovering the texture, namely recording texture coordinates corresponding to the top points of the contraction edges, so that after the simplified first furniture model is recovered into the target furniture model, the texture of the target furniture model is recovered according to the texture coordinates. If the user feels that the loss of appearance of the simplified model is too severe, the degree to which the mesh model is desired to be restored may be input until satisfied.
In the method provided in the embodiment of the present application, the simplification result is shown in fig. 7, fig. 7 shows effect graphs of different simplification degrees for the same furniture model, the first row of the model in fig. 7 is the target furniture model, the second row is the model simplification result corresponding to different simplification rates (corresponding to different numbers of triangular faces, the number of the triangular faces of the original model in the graph is 2,137,284, and the number of the simplified triangular faces is the product of the number of the triangular faces of the original model and the simplification rate), it can be seen that the models in different fineness degrees can maintain better appearance effect, and the model simplification effect corresponding to the simplification rate is output according to the simplification degree desired by the user. Compared with the prior art, the method can quickly and effectively simplify the furniture three-dimensional model and keep the geometric characteristics and the texture characteristics of the model, simplifies and limits texture seams, and avoids the problem of serious texture distortion caused by simplification.
For easy understanding, please refer to fig. 8, which provides a model mesh optimization apparatus based on 3D model texture, including:
the reading module is used for reading the target furniture model and acquiring the grid model information and the texture information of the target furniture model;
the simplification module is used for carrying out grid simplification on the target furniture model according to the target simplification rate and the edge simplification priority input by the user to obtain a simplified first furniture model, the grid simplification is constrained by an edge contraction constraint condition, and the edge contraction constraint condition is as follows:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, and ε is a threshold.
Further, still include: a detection module;
and the detection module is used for detecting whether a new target simplification rate is received or not, if so, restoring the simplified first furniture model into a target furniture model, and then carrying out grid simplification on the target furniture model according to the new target simplification rate and the edge simplification priority to obtain a simplified second furniture model.
Further, the system also comprises an edge energy calculation module;
an edge energy calculation module to:
determining edge merging vertexes based on the energy loss of the geometric features of the minimized edges according to the mesh model information to obtain a contracted edge;
calculating texture seam loss and symmetric texture factors of the contraction edge;
calculating the energy of each edge according to the geometric characteristic energy loss, the texture seam loss and the symmetrical texture factor of the contraction edge, wherein the energy calculation formula is as follows:
Eedge＝λEshape+(1+λ)Eseam+δ
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeIs edge geometryCharacteristic energy loss, EseamFor texture seam loss, δ is the symmetric texture factor;
edge reduction priorities are determined from the energy of each edge, with lower energy edges having higher pinch priorities.
Further, the calculation formula of the edge geometric characteristic energy loss is as follows:
where w (-) is a weight function of a monotonically increasing function with respect to the triangle area S, df(v) Point-to-face distance, N, from vertex v to face fF(v) All adjacent surfaces of the vertex v, each edge passing through a minimum EshapeThe optimal edge merging vertex v can be obtainednew。
Further, the texture seam loss of the shrink edge is calculated by the formula:
wherein v is0And v1Is a seam edge v0v1T is transposed.
Further, the symmetric texture factors are:
where Ω is the set of edges.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer system (which may be a personal computer, a server, or a network system) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (8)
1. A model mesh optimization method based on 3D model texture is characterized by comprising the following steps:
reading a target furniture model, and acquiring grid model information and texture information of the target furniture model;
performing grid simplification on the target furniture model according to a target simplification rate and an edge simplification priority input by a user to obtain a simplified first furniture model, wherein the grid simplification is constrained by an edge contraction constraint condition, and the edge contraction constraint condition is as follows:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, ε is a threshold, w (-) is a weight function of a monotonically increasing function related to the triangle area S, df(v) Is the vertex v to the facePoint-to-surface distance of f, NF(v) All adjacent surfaces of the vertex v, each edge passing through a minimum EshapeThe optimal edge merging vertex v can be obtainednew，v1And v2To a contracted side v1v2Two vertex coordinates of SfIs the area of the triangular face f; v. of0And v1Is a seam edge v0v1T is transposed.
2. The model mesh optimization method based on 3D model texture according to claim 1, wherein the mesh simplification is performed on the target furniture model according to a target simplification rate and an edge simplification priority input by a user to obtain a simplified first furniture model, and then further comprising:
and detecting whether a new target simplification rate is received, if so, restoring the simplified first furniture model into the target furniture model, and then carrying out grid simplification on the target furniture model according to the new target simplification rate and the edge simplification priority to obtain a simplified second furniture model.
3. The model mesh optimization method based on 3D model texture according to claim 1, wherein after the target furniture model is read and the mesh model information and the texture information of the target furniture model are obtained, mesh simplification is performed on the target furniture model according to a target simplification rate and an edge simplification priority input by a user to obtain a simplified first furniture model, before further comprising:
determining edge merging vertexes based on the energy loss of the minimum edge geometric characteristics according to the mesh model information to obtain a contracted edge;
calculating texture seam loss and symmetric texture factors of the contraction edge;
calculating the energy of each edge according to the geometric characteristic energy loss of the contraction edge, the texture seam loss and the symmetrical texture factor, wherein the energy calculation formula is as follows:
Eedge＝λEshape+(1+λ)Eseam+δ
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeFor edge geometry characteristic energy losses, EseamFor texture seam loss, δ is the symmetric texture factor;
edge reduction priorities are determined from the energy of each edge, with lower energy edges having higher pinch priorities.
4. The model mesh optimization method based on 3D model texture, according to claim 3, characterized in that the symmetric texture factors are:
where Ω is the set of edges.
5. The model mesh optimization method based on 3D model texture according to claim 2, wherein the mesh simplification of the target furniture model according to the target simplification rate and the edge simplification priority input by the user to obtain the simplified first furniture model further comprises:
and recording texture coordinates corresponding to the top points of the contraction edges, so that after the simplified first furniture model is restored into the target furniture model, the texture of the target furniture model is restored according to the texture coordinates.
6. A model mesh optimization device based on 3D model texture, comprising:
the reading module is used for reading a target furniture model and acquiring grid model information and texture information of the target furniture model;
a simplification module, configured to perform mesh simplification on the target furniture model according to a target simplification rate and an edge simplification priority input by a user, to obtain a simplified first furniture model, where the mesh simplification is constrained by an edge contraction constraint condition, where the edge contraction constraint condition is:
wherein e isjFor the jth edge of the mesh model, Eshape(ej) Is ejThe energy loss of the geometric features is reduced,
for maximum geometric characteristic energy loss, Eseam(ej) Is ejα is a preset weight coefficient, ε is a threshold, w (-) is a weight function of a monotonically increasing function related to the triangle area S, df(v) Point-to-face distance, N, from vertex v to face fF(v) All adjacent surfaces of the vertex v, each edge passing through a minimum EshapeThe optimal edge merging vertex v can be obtainednew，v1And v2To a contracted side v1v2Two vertex coordinates of SfIs the area of the triangular face f; v. of0And v1Is a seam edge v0v1T is transposed.
7. The apparatus for model mesh optimization based on 3D model texture as claimed in claim 6, further comprising: a detection module;
the detection module is used for detecting whether a new target simplification rate is received or not, if yes, the simplified first furniture model is restored to the target furniture model, and then grid simplification is carried out on the target furniture model according to the new target simplification rate and the edge simplification priority, so that a simplified second furniture model is obtained.
8. The model mesh optimization device based on 3D model texture as claimed in claim 6, further comprising an edge energy calculation module;
the edge energy calculation module is configured to:
determining edge merging vertexes based on the energy loss of the minimum edge geometric characteristics according to the mesh model information to obtain a contracted edge;
calculating texture seam loss and symmetric texture factors of the contraction edge;
calculating the energy of each edge according to the geometric characteristic energy loss of the contraction edge, the texture seam loss and the symmetrical texture factor, wherein the energy calculation formula is as follows:
Eedge＝λEshape+(1+λ)Eseam+δ
wherein, λ is weight coefficient, λ is more than or equal to 0 and less than or equal to 1, EshapeFor edge geometry characteristic energy losses, EseamFor texture seam loss, δ is the symmetric texture factor;
edge reduction priorities are determined from the energy of each edge, with lower energy edges having higher pinch priorities.
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