CN109801367A - A kind of grid model feature edit method based on compression manifold mode - Google Patents
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Abstract
The invention discloses a kind of grid model feature edit methods based on compression manifold mode, comprising steps of 1) obtaining the basic parameter of triangle grid model；2) calculating is reconstructed to triangle grid model using compression manifold mode, obtains the feature skeleton pattern of triangle grid model；3) according to user interactive operation, deformation editor is carried out to the feature skeleton pattern of triangle grid model, the edited skeleton pattern of deformation is obtained by calculation；4) skeleton pattern smoothing processing is carried out by calculating to the edited skeleton pattern of deformation；5) grid model details is added according to feature skeleton pattern of the feature skeleton pattern of former pessimistic concurrency control construction to deformation editor；6) grid model of the differential coordinate pair addition details based on former grid model is repaired, and obtains deforming edited grid model.The present invention realizes the feature skeleton based on compression manifold schema construction grid model for the first time, and using the differential coordinate for keeping former grid model, so that edited grid model is truer.
Description
Technical field
The present invention relates to the technical fields of Digital Geometry Processing, refer in particular to a kind of grid mould based on compression manifold mode
Type feature edit method.
Background technique
In the present age, with the high speed development of science and technology, computer field is also in fast development with rapid changepl. never-ending changes and improvements, as hardware is led
The breakthrough in domain, software field are also fast-developing.People's lives are improved, and also occur in people's lives more and more
High-tech product, wherein have a large amount of sci-tech product be originated from computer graphics.Three-dimensional animation film from video display amusement
With the various high-tech technologies such as the scene of game of the great sense of reality, virtual experimental, simulated scenario analyzes the producing scientific research such as data neck
Domain, appliance computer computer aided geometric design carry out PRODUCT FORM DESIGN etc., it has been found that 3-dimensional digital geometrical model is more next
More industry fields are widely used.People also increasingly pay close attention to 3-dimensional digital geometrical model, in building three-dimensional geometry mould
During type, it has been found that many mathematics geometrical issues to be treated would generally be related to, for example, denoising to data
Processing (denoising) carries out simplified processing (simplification) to data, to data parameterization
(parameterization), the segmentation of deformation editor (the deformation or editing), grid model of grid model
(segmentation), the problems such as shape analysis and retrieval (the shape analysis and retrieval) of grid model.
These problems i.e. the main problem of Digital Geometry Processing research processing, they constitute the main of Digital Geometry Processing research
Content.We are indicated a three-dimension object by computer, it usually needs the expression of its geometrical model is obtained, it is right
One geometric object can be expressed by spline function mathematically or Implicitly function.We using building threedimensional model as
The basis of computer graphics is the premise of computer graphics study other problems.The building that we are understood at present is three-dimensional
The method of model has very much, can carry out computer using NURBS (non-uniform rational B- batten, Bezier curve curved surface) method
Computer Aided Design (CAD)；Also it can use the building that 3 d modeling software Autodesk 3D Maxs directly carries out model manually；Also
The reconstruction etc. of model can be completed by the acquisition of cloud by depth camera to model scanning point cloud.Although having at present a large amount of
Threedimensional model building method, but use relatively cumbersome complexity, be not particularly suited for general domestic consumer be used to construct three-dimensional
Model.
Comparatively difficulty is larger for direct construction threedimensional model, and people then expect modifying to existing threedimensional model
Editor obtains satisfactory model.Operation can save the plenty of time in this way, improve the efficiency that threedimensional model building generates, promoted
The recycling rate of waterused of threedimensional model.It is desirable to only need the operation of simple circumgyration stretch to model i.e. to can reach to three-dimensional
The effect of model editing.Therefore, while how keeping the topological structure of archetype, how effectively and intuitively to 3D model
Carrying out gridding edition processing is one of research contents in Digital Geometry Processing.
Due to the extensive use of three-dimensional grid model, people meet oneself using existing three-dimensional grid model to produce
It is required that three-dimensional grid model, therefore to the deformation of three-dimensional grid model editor have certain requirement.It is desirable to pass through grid
Deformation editor obtains the preferable three-dimensional grid model of quality, while reducing the complexity operated to grid model, and people can letter
It is single that editing and processing efficiently is carried out to grid model.Therefore, judging has two o'clock for the Standard General of gridding edition algorithm, and first
The quality that three-dimensional grid model quality is obtained after three-dimensional grid model deformation editor, second be user to three-dimensional grid model into
During row distortion of the mesh is edited, the complexity of all operations.
Summary of the invention
The purpose of the present invention is to overcome the shortcomings of the existing technology with it is insufficient, propose a kind of based on compression manifold mode
Grid model feature edit method realizes the feature skeleton pattern based on compression manifold schema construction grid model, to net for the first time
Lattice model carries out feature edit, and using the differential coordinate for keeping former grid model, so that edited grid model is trueer
It is real.
To achieve the above object, a kind of technical solution provided by the present invention are as follows: grid mould based on compression manifold mode
Type feature edit method, comprising the following steps:
1) basic parameter of triangle grid model is obtained；
2) calculating is reconstructed to triangle grid model using compression manifold mode, obtains the feature bone of triangle grid model
Frame model；
3) according to user interactive operation, deformation editor is carried out to the feature skeleton pattern of triangle grid model, passes through calculating
It obtains deforming edited skeleton pattern；
4) skeleton pattern smoothing processing is carried out by calculating to the edited skeleton pattern of deformation；
5) grid model is added according to feature skeleton pattern of the feature skeleton pattern of former pessimistic concurrency control construction to deformation editor
Details；
6) grid model of the differential coordinate pair addition details based on former grid model is repaired, after obtaining deformation editor
Grid model.
In step 1), the basic parameter of triangle grid model include point position, connection relationship between points and
Each face forms combination a little.
In step 2), triangle grid model is by compression manifold pattern refactoring feature skeleton pattern, by calculating one
The preceding m feature vector of the compression manifold base of original mesh model M with n vertex constructs the feature skeleton of grid model
Model, formula are as follows:
In formula, αx,αy,αzTo indicate the characteristic value for compressing manifold base of original mesh model M.φ1,...,φnTo indicate
The feature vector of the compression manifold base of original mesh model M.It respectively indicates and is reconstructed according to m characteristic value feature vector
Grid model x, y, z sit target value.The feature skeleton pattern for constructing grid, needs m before taking feature vectors, and m is less than
n；Wherein, φ1,...,φmIt is the preceding m feature vector of M, then ni={ fx(vi),fy(vi),fz(vi), formula indicates vertex
niBy vertex viPass through functionFor i=
1,…,n；The grid model S=S constructed by m feature vectorm, connectivity is identical as grid model M, claims grid model Sm
For the feature skeleton pattern of former grid model M.
In step 3), user selects the net region for wishing to deform, i.e. region of interest ROI, VROI indicates the region
In vertex set, alternative types needed for user specifies area-of-interest can be translation type or rotation type, then,
User indicates that target configures by the way that some point is dragged to target position.
In step 4), go out to minimize E pairs of energy function by using the preceding m characteristics of low-frequency construction of function of grid model
Grid model feature skeleton pattern is smoothed, and formula is as follows:
In formula, E is energy function.AjBe byIt reconstructs,For's
Characteristic value.For modelOn vertex.φj[i] is vertex viOn j-th of characteristic function φjValue, φjFor grid model
Preceding j characteristics of low-frequency function,To deform edited grid model feature skeleton pattern vertex.Smooth change in order to obtain
Shape skeleton pattern, it is intended that be eachFind a smooth approximationEach vertexTo obtain improved deformation skeleton pattern S*.FunctionWherein a
∈ { x, y, z } is the function M → R inputted on the M of surface.
In step 5), grid model details is added to the feature skeleton pattern of deformation, comprising the following steps:
5.1) when creating primitive character skeleton pattern S, to the vertex v of original mesh modeliWith according to original mesh model
The vertex n of the feature skeleton pattern S of buildingiBetween difference done calculate and store,For the details vector provided；
5.2) details vector is added to the feature skeleton pattern of deformation.
In step 6), according to the differential coordinate of former grid model, so that the feature skeleton pattern of addition details vector is protected
Hold the differential coordinate of former grid model, comprising the following steps:
6.1) the differential coordinate of former grid model is calculated；
6.2) details vector is added according to the differential coordinate of archetype M and smooth deformed feature skeleton patternAfterwards
Apex coordinate V, solve the apex coordinate V' for keeping former grid model after deformation, obtain edited grid model.
Compared with prior art, the present invention having the following advantages that and beneficial effect；
1, the present invention realizes the feature skeleton pattern based on compression manifold schema construction grid model for the first time, grid model
Feature skeleton pattern maintains original mesh mould contour feature, realizes better choice model part.Locality is preferable
Compression manifold mode is applied to the deformation editor of three-dimensional grid model.Grid in research and improvement triangle grid model gridding edition
The recovery of details, to design more efficient, more natural grid model gridding edition effect.
2, finding out influences gridding edition deformation effect, calculation amount and editor in present triangle grid model gridding edition algorithm
The key component of efficiency.The feature skeleton pattern of research compression manifold mode construction triangle grid model, to triangle grid model
Gridding edition is carried out, how model is deformed without influencing details in editing process, carries out in-depth study.
3, in construction grid model feature skeleton pattern, difference can be caused by carrying out deformation using the feature vector of different number
The variation of scale will lead to the change in shape of global level, by the feature skeleton pattern of preceding several feature vector creations only in order to catch
Localized variation is obtained, more feature vectors are needed.The selection of research characteristic vector meets gridding edition requirement more to construct
Good feature skeleton pattern.
4, area-of-interest is translated and is rotated when gridding edition, the presence at region of interest border is caused not connect
How continuous phenomenon, research carry out better smoothing processing to boundary to after the deformation of feature skeleton pattern.
5, due to having only used the feature skeleton pattern of a small amount of feature vector tectonic model, deformed feature skeleton pattern
Lack the details of original mesh model, how the details of master mould is added to the feature according to original mesh Construction of A Model by research
On skeleton pattern, edited grid model is obtained.
6, the present invention is for the first time in restoring particular procedures, using the differential coordinate for keeping former grid model, so that after editor
Grid model it is truer.
7, the method for the present invention has extensive use space easy to operate, adaptable in gridding edition.
Detailed description of the invention
Fig. 1 is logical flow diagram of the present invention.
Fig. 2 is grid model continuous structure figure of the present invention.
Fig. 3 is that selected editing area deforms schematic diagram.
Fig. 4 is characterized skeleton pattern deformation schematic diagram.
Fig. 5 is characterized skeleton pattern and deforms smooth schematic diagram.
Specific embodiment
The present invention is further explained in the light of specific embodiments.
As depicted in figs. 1 and 2, the grid model feature edit side based on compression manifold mode provided by the present embodiment
Method, concrete condition are as follows:
The first step constructs the feature skeleton pattern of grid model
Compression manifold pattern feature function is that the quadractically integrable function defined in original mesh model M forms a base.
Similar to Fourier's harmonic wave of curved surface superior function, the compression manifold pattern feature function with lower characteristic value corresponds to Low-frequency Modes
Formula, and the compression manifold pattern feature function with higher feature value corresponds to the details of high frequency mode description input manifold M.It is defeated
Entering is the triangular mesh for being similar to hidden face M.In this case, it would be desirable to from this grid computing go out from
The compression manifold mode for the form of dissipating.Compression manifold mode of grid itself and its characteristic value have been proved to be able to converge to hidden
The manifold for hiding manifold, because grid has preferably approached manifold.Since higher characteristic function has higher frequency and therefore
Smaller details is captured, so the quantity (i.e. using only a small amount of feature vector) of characteristic function can be truncated to reconstruct table in we
Face is to obtain different degrees of details.
Given one surface mesh with n vertex, is also indicated with M, we calculate the feature for compressing manifold base of M to
Amount, uses φ1,...,φnTo indicate.The feature skeleton pattern of grid is constructed, we only need the feature vector that m is a before taking, and (m is remote
Less than n).By reconstructing being abstracted that give our higher level its rough features of surface capture.Specifically, enabling N
={ n1,n2,…,nnIt is that preceding m feature vector φ is used only1,...,φmFrom the vertex set V={ v of M1,v2,…,vnReconstruct
Point set.Wherein φ1,...,φmIt is the preceding m feature vector of M.
So ni={ fx(vi),fx(vi),fx(vi) for i=1 ..., n.The grid mould constructed by m feature vector
Type S=Sm, vertex ni, connectivity is identical as grid model M.We claim grid model SmFor the feature of former grid model M
Skeleton pattern.
Finally, due to which higher characteristic function has higher frequency and therefore captures smaller details, so we can
Carry out reconstructing surface so that the quantity (i.e. using only least coordinate weight) of characteristic function is truncated to obtain different degrees of details.
The feature skeleton pattern that grid model how is constructed for grid model, to the selection of feature vector number than heavier
It wants.General different feature vector can capture the details of different scale.Therefore, it is deformed using the feature vector of different number
It can cause the variation of different scale.
In general, only will lead to the shape of grid model entirety by the feature skeleton pattern of most preceding several feature vector creations
Shape variation.In order to capture localized variation, it would be desirable to more feature vectors.Specifically, if area-of-interest R very little,
So we need more feature vectors to construct skeleton pattern, and R is reasonably reconstructed in this skeleton pattern in this way, and
And the variation of corresponding coordinate weight is enough to deform R.If the feature vector that we select is very little, the feature skeleton pattern of ear
Type substantially collapses a bit, can not show ear at all.It is deformed due to being calculated for feature skeleton pattern, so cannot be as
Skeleton pattern describes the deformation of ear.Using more feature vectors, we can capture the ear in bone, and further
Deformation.
On the other hand, if interested region is very big, it is generally necessary to be changed within a large range.If
We have selected too many feature vector now, minimize the office that energy function attempts keeping characteristics skeleton pattern in step 2
Portion's details is (because there is more terms, i.e., with the A of big jj, they are described).Roughly, the power of lower feature vector
The optimization of weight is flooded by a large amount of higher feature vector.Therefore, the deformation of the feature skeleton pattern returned in step 2 becomes
To in having some theatrical variations on several points when attempting to retain local detail elsewhere.Therefore, a wide range of
In the case where, it would be desirable to select a small amount of feature vector to carry out construction feature skeleton pattern, to emphasize the weight of global deformation.
In short, the number of the feature vector for reconstruction features skeleton pattern should be selected according to the size of area-of-interest R
Mesh.
Second step guesses deformed grid model
Firstly, user selects him to wish the net region of deformation.We term it region of interest ROI, VROI is indicated should
Vertex set in region.Next, alternative types needed for the specified area-of-interest of user, can be translation type or rotation
Turn type.Then, user indicates that target is configured by the way that some point (such as v belongs to VROI) is simply dragged to target position.
The alternative types combined from the position of v sum, if it is desired to transformation be translation type, then our algorithm calculates flat
The amount of shifting toOr rotary shaft p and spin matrix r, if it is desired to transformation be rotation type, then our uses with
Simple process configures down to calculate the coarse target of feature skeleton pattern SFor all point viIt is not belonging to VR, it is corresponding
Point piTarget position be simply in feature skeleton patternFor each point viBelong to VR, if the type of transformation is
Translation, then target position isIf alternative types are rotations, target position is
In other words, we only shear interested region, and are applied to the object transformation of user's instruction, and its
Remaining shape remains unchanged.It is certainly unsatisfactory to the preliminary conjecture of target configuration in this way.In fact, deformation is not continuous
(along the boundary of influence area R, there are significant, discontinuous variations for deformation).Odd number, we are later it will be seen that
In two steps, our algorithm uses this initial target configuration, and produces one preferably, the feature bone of smooth curved
Frame model.By taking Fig. 3 as an example: the body in order to be bent dragon, we specify a rotation in the latter half of dragon.Then, we will
This rotation is applied to the entire area-of-interest in feature skeleton pattern, obtains deformed grid model.
Notice that translating type and rotary-type movement only generate the specified motion mode of final deformation in step 2.Final
Deformation is not necessarily rigid.
Third step, the feature skeleton pattern deformation of grid model
For feature skeleton pattern S, we, which have, guesses deformed object module.In this step, it is intended that
From the deformed object module of conjectureTo the target distortion feature skeleton pattern S of computed improved*.In the step 3 of next section description
In, we will be to S*Addition details inputs the textured surface M of surface M to obtain*。
Fig. 2 illustrates continuous structure.
It is to guess i-th of vertex v in target skeleton pattern after grid model construction feature skeleton pattern deformsiPosition.
The coordinate function of conjecture target skeleton pattern is considered nowNote that each functionWherein a ∈ { x, y, z } is
Input function M → R on the M of surface.The skeleton pattern changed by circumgyration stretchIt is usually undesirable.Particularly, by cutting
It cuts influence area and simply translates and rotate the part, there are discontinuities for the boundary in influence area.In other words, whole
The not smooth transition of a editing.This means that coordinate functionIt is unsmooth in cutting process.Smooth deformation in order to obtain
Skeleton pattern, it is intended that be eachFind a smooth approximationEach vertexTo obtain improved deformation skeleton pattern S*。
Thus, it is noted that since the characteristic function of M constitutes the basis of quadractically integrable function race on M, each faIt can write
At all characteristic function φiThe linear combination of s, in addition, the characteristic function of low characteristic value is similar to low frequency mode, and high characteristic value
Characteristic function correspond to high frequency mode.Since our target is to obtain faSmooth reconstruct, so we will ignore high frequency
Mode.Therefore, it has been found that m characteristics of low-frequency function phi before only using1,…,φm.WhereinIt is desirable that finding the weight for minimizing energy functionWherein φj[i] is vertex viOn j-th of characteristic function φjValue:
Intuitively, guess deformed object moduleCoordinate in discontinuity require high-frequency characteristic function to weigh
Structure it, and be used only low frequency mode can generate it is smootherThis causes preferably to deform skeleton pattern S*.Referring to fig. 4,
After step 2 from new coordinate weightThe skeleton pattern of reconstruction shows flat from area-of-interest to rest part
It slips over and crosses.
Deformed feature skeleton patternCoordinate in discontinuity require high-frequency characteristic function to reconstruct it, and
It can be generated using only low frequency mode smootherThis causes preferably to deform skeleton pattern S*.Referring to Fig. 5, from new coordinate
WeightThe skeleton pattern of reconstruction shows the smooth transition from area-of-interest to rest part.
Minimum processing is carried out to energy function E.There is 3m variable in energy function in equation (2).In order to minimize
E, we calculate it about AkGradient
WhereinIt is the coordinate function for guessing target skeleton pattern.Now, we obtain all AkPartial derivative
It is zero.This causes the form of system of linear equations as follows: Φ A*=b, wherein Φ is m m matrix, Φi,j=< φi·φj>2, A*It is
One matrix of m × 3,With b and matrix of m × 3, wherein the i-th behaviorMake
Use A*As coordinate weight, we rebuild new deformation behaviour skeleton pattern S*。
4th step restores the details of grid model
We are now with the smoothed out feature skeleton pattern S of deformation*.Several feature vector constructions before being only used due to us
The feature skeleton pattern of original mesh model simultaneously deforms it, so this feature skeleton pattern lacks original mesh model
Minutia.We need details being added to feature skeleton pattern S by calculating*On, obtain the grid M of deformation*.In order to
The shape details for tracking grid model, when creating primitive character skeleton pattern S, our vertex vs to original mesh modeliWith
According to the vertex n of the feature skeleton pattern S of original mesh model constructioniBetween difference done calculate and store.We term it
ByFor the details vector provided.
5th step restores grid model details based on differential coordinate
When grid model addsWhen, the part of grid model is stretched, and model is caused to deform, can be by deformed net
Lattice model keeps the differential coordinate of former grid model to restore to obtain deformed grid model.
According to Laplacian matrix, by transition matrix, available following equation:
LV'=δ
L is the Laplacian matrix of the apex coordinate of original mesh model in equation, and V ' is deformed apex coordinate, δ
The differential coordinate of coordinate is done for vertex.
According to the differential coordinate of archetype M and smooth deformed feature skeleton pattern additionApex coordinate V afterwards,
Solve the apex coordinate V' that former grid model is kept after deforming.By observing the transition matrix, it is found that it is unusual, i.e. matrix
Order be less than n (number on vertex), be n-k, wherein k is the quantity for the part being connected in archetype M.
In order to make entire linear system have solution, the apex coordinate V' deformed to the end is obtained, it is assumed that M is connection, i.e. k is 1,
We need the cartesian coordinate at least one vertex to determine spatial position.And these apex coordinates are used as constraint in equation
Condition makes linear system have solution, spatially, as obligatory point, controls the deformation of entire grid model.Enable known constraints
The collection of point is combined into C, that is, has additional constraint are as follows:
vj=cj,j∈C
Remember C={ 1,2 ..., m }, that is, there is m control point, available following system of linear equations:
After obtaining new transition matrix, to the index value on constraint vertex, constant term is added in corresponding position on the right of equation.
In this way, entire linear system is in sequency spectrum, is solved by the principle of least square, obtain result to the end.
Least square method (also known as least squares method) is a kind of mathematical optimization techniques.It passes through the quadratic sum for minimizing error
Find the optimal function matching of data.Unknown data can be easily acquired using least square method, and these are acquired
Data and real data between error quadratic sum be minimum.According to the principle of least square, the energy shift on control point is real
It has uniformly been diffused into entire grid on border, has finally obtained the distorted pattern for keeping former grid model differential coordinate.
It is indicated with optimization formula:
We remember that plus the L matrix after known m obligatory point information be L', and it is δ ' that the δ on the right, which also accordingly expands, then formula
LV'=δ just becomes:
L'V'=δ '
L' ranks are (m+n) × n, and L' ranks are n × 3, and the ranks of δ ' are then (m+n) × 3, are thought with least square method
Think, the transposed matrix (L') of equation both sides while premultiplication L'T:
(((L')T) L') V'=((L')T)δ'
As the solving speed of Large sparse matrix is greatly speeded up, whole deformation adds grid model particular procedures efficiency
Also it will improve, and finally obtain the edited grid model of deformation.
Embodiment described above is only the preferred embodiments of the invention, and but not intended to limit the scope of the present invention, therefore
All shapes according to the present invention change made by principle, should all be included within the scope of protection of the present invention.
Claims (7)
1. a kind of grid model feature edit method based on compression manifold mode, which comprises the following steps:
1) basic parameter of triangle grid model is obtained；
2) calculating is reconstructed to triangle grid model using compression manifold mode, obtains the feature skeleton pattern of triangle grid model
Type；
3) according to user interactive operation, deformation editor is carried out to the feature skeleton pattern of triangle grid model, is obtained by calculation
Deform edited skeleton pattern；
4) skeleton pattern smoothing processing is carried out by calculating to the edited skeleton pattern of deformation；
5) grid model details is added according to feature skeleton pattern of the feature skeleton pattern of former pessimistic concurrency control construction to deformation editor；
6) grid model of the differential coordinate pair addition details based on former grid model is repaired, and obtains deforming edited net
Lattice model.
2. a kind of grid model feature edit method based on compression manifold mode according to claim 1, feature exist
In: in step 1), the basic parameter of triangle grid model includes position, connection relationship between points and each face of point
Form combination a little.
3. a kind of grid model feature edit method based on compression manifold mode according to claim 1, feature exist
In: in step 2), triangle grid model has n by compression manifold pattern refactoring feature skeleton pattern, by calculating one
The preceding m feature vector of the compression manifold base of the original mesh model M on a vertex constructs the feature skeleton pattern of grid model,
Formula is as follows:
In formula, αx,αy,αzTo indicate the characteristic value for compressing manifold base of original mesh model M；φ1,...,φnTo indicate original
The feature vector of the compression manifold base of grid model M；Respectively indicate the net reconstructed according to m characteristic value feature vector
The x, y, z of lattice model sits target value；The feature skeleton pattern for constructing grid, needs m before taking feature vectors, and m is less than n；Its
In, φ1,...,φmIt is the preceding m feature vector of M, then ni={ fx(vi),fy(vi),fz(vi), formula indicates vertex niBy
Vertex viPass through functionFor i=1 ..., n；
The grid model S=S constructed by m feature vectorm, connectivity is identical as grid model M, claims grid model SmFor former net
The feature skeleton pattern of lattice model M.
4. a kind of grid model feature edit method based on compression manifold mode according to claim 1, feature exist
In: in step 3), user selects the net region for wishing to deform, i.e. region of interest ROI, VROI indicates the top in the region
Point set, alternative types needed for user specifies area-of-interest can be translation type or rotation type, then, Yong Hutong
It crosses and some point is dragged to target position to indicate that target configures.
5. a kind of grid model feature edit method based on compression manifold mode according to claim 1, feature exist
In: in step 4), go out to minimize energy function E to grid by using the preceding m characteristics of low-frequency construction of function of grid model
Aspect of model skeleton pattern is smoothed, and formula is as follows:
In formula, E is energy function；AjBe byIt reconstructs,ForFeature
Value；For modelOn vertex；φj[i] is vertex viOn j-th of characteristic function φjValue, φjFor the preceding j of grid model
A characteristics of low-frequency function,To deform edited grid model feature skeleton pattern vertex；Smooth deformation bone in order to obtain
Frame model, it is desirable to be eachFind a smooth approximationEach vertexTo
Obtain improved deformation skeleton pattern S*；FunctionWherein a ∈ { x, y, z } is the function M inputted on the M of surface
→R。
6. a kind of grid model feature edit method based on compression manifold mode according to claim 1, feature exist
In: in step 5), grid model details is added to the feature skeleton pattern of deformation, comprising the following steps:
5.1) when creating primitive character skeleton pattern S, to the vertex v of original mesh modeliWith according to original mesh model construction
The vertex n of feature skeleton pattern SiBetween difference done calculate and store,For the details vector provided；
5.2) details vector is added to the feature skeleton pattern of deformation.
7. a kind of grid model feature edit method based on compression manifold mode according to claim 1, feature exist
In: in step 6), according to the differential coordinate of former grid model, so that the feature skeleton pattern of addition details vector keeps former net
The differential coordinate of lattice model, comprising the following steps:
6.1) the differential coordinate of former grid model is calculated；
6.2) details vector is added according to the differential coordinate of archetype M and smooth deformed feature skeleton patternTop afterwards
Point coordinate V solves the apex coordinate V' of the former grid model of holding after deformation, obtains edited grid model.
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| CN112462689A (en) * | 2020-12-10 | 2021-03-09 | 德州钰雕机械设备有限公司 | Method for generating handicraft digital model random carving four-axis three-linkage cutter path |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6452596B1 (en) * | 1998-10-06 | 2002-09-17 | International Business Machines Corporation | Methods and apparatus for the efficient compression of non-manifold polygonal meshes |
| CN101261741A (en) * | 2007-10-19 | 2008-09-10 | 北京航空航天大学 | A physical distortion method based on details coding and reconstruction |
| CN101354788A (en) * | 2008-08-20 | 2009-01-28 | 大连民族学院 | One-dimensional nondestructive geometric compressing method of three-dimensional grid model |
| CN102509356A (en) * | 2011-11-10 | 2012-06-20 | 杭州电子科技大学 | Detail-kept geometrical model deformation method using grid subdivision |
| CN103688548A (en) * | 2011-07-08 | 2014-03-26 | 汤姆逊许可公司 | System and method for encoding and decoding a bitstream for a 3D model having repetitive structure |
| CN107888915A (en) * | 2017-11-07 | 2018-04-06 | 武汉大学 | A kind of perception compression method of combination dictionary learning and image block |
| CN109299569A (en) * | 2018-10-24 | 2019-02-01 | 广州市香港科大霍英东研究院 | A kind of Large eddy simulation method of the incompressible viscous flows body based on coherent structure |
-
2019
- 2019-02-25 CN CN201910135990.2A patent/CN109801367B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6452596B1 (en) * | 1998-10-06 | 2002-09-17 | International Business Machines Corporation | Methods and apparatus for the efficient compression of non-manifold polygonal meshes |
| CN101261741A (en) * | 2007-10-19 | 2008-09-10 | 北京航空航天大学 | A physical distortion method based on details coding and reconstruction |
| CN101354788A (en) * | 2008-08-20 | 2009-01-28 | 大连民族学院 | One-dimensional nondestructive geometric compressing method of three-dimensional grid model |
| CN103688548A (en) * | 2011-07-08 | 2014-03-26 | 汤姆逊许可公司 | System and method for encoding and decoding a bitstream for a 3D model having repetitive structure |
| CN102509356A (en) * | 2011-11-10 | 2012-06-20 | 杭州电子科技大学 | Detail-kept geometrical model deformation method using grid subdivision |
| CN107888915A (en) * | 2017-11-07 | 2018-04-06 | 武汉大学 | A kind of perception compression method of combination dictionary learning and image block |
| CN109299569A (en) * | 2018-10-24 | 2019-02-01 | 广州市香港科大霍英东研究院 | A kind of Large eddy simulation method of the incompressible viscous flows body based on coherent structure |
Non-Patent Citations (1)
| Title |
|---|
| 陈安龙 等: "基于小波和偶合特征的多数据流压缩算法", 《JOURNAL OF SOFTWARE》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112462689A (en) * | 2020-12-10 | 2021-03-09 | 德州钰雕机械设备有限公司 | Method for generating handicraft digital model random carving four-axis three-linkage cutter path |
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