CN101197049B - Full-automatic driving method of three-dimensional motion model based on three-dimensional motion parameter - Google Patents
Full-automatic driving method of three-dimensional motion model based on three-dimensional motion parameter Download PDFInfo
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Abstract
The invention discloses a full-automatic driving method for a three-dimensional movement model based on three-dimensional movement parameters. At first, a movement information file is read, the movement data is restored, and an initial bone template is obtained; then the extraction of skeleton lines is done for the model given by the user, and the candidate arthrosis points are marked; the corresponding arthrosis points are automatically matched; the automatic binding of the bone and the skin is done to finish the distribution of bone weight at the top of the skin. The invention assures the effect of automatic extraction and matching as well as the execution time, greatly saves the driving time of the model, and saves manpower and material resources.
Description
Technical field
The present invention relates to electronic information technical field, especially computer vision field.
Background technology
The three-dimensional model Driving technique is in industrial design, product development, and medical research, CAD of Garment, there is wide application prospect in fields such as computer animation design.Current, it is very fast that dimensional Modeling Technology develops, and various modeling methods emerge in an endless stream, but will make the model sport of building up, and but is not that part is easy to thing.Traditional way is: use business software (as 3Dmax, Maya etc.) carry out Geometric Modeling earlier, manually demarcate frame position then, the model surface vertex weights is set, obtain model, realize animation effect by reading in external movement data (as motion capture data) based on skeleton.This method can realize animation effect more true to nature, but limitation is very big: method depends on veteran animation teacher, and the construction cycle is longer, if the visual human reaches certain scale, its workload is very big.Also have some model driven methods, " use fuzzy clustering and cut apart the decomposition multi-layer net " (Katz S of delivering at " ACM figure journal " of Katz S and Tal A 2003 for example, Tal A.Hierarchical meshdecomposition using fuzzy clustering and cuts[J] .ACM Trans on Graphics, 2003,22 (3): 954-961.) people such as disclosed surface model division methods or Yang Changshui " the personalized virtual human body model skeleton generation method " delivered at 2004 " computer-aided design (CAD) and graphics journal " are disclosed with methods such as model piecemeals, essence all is the joint of extracting between each piecemeal, matches then on the standard bone shut die plate.This model driven method based on division and piecemeal also all needs a large amount of user's operations.
The automatic driving method of three-dimensional (3 D) manikin, the core methed that relates to mainly contains: mate automatically in model skeletal extraction and joint, skin deformation etc.
Skeletal extraction is to extract skeleton line from model, and according to geometric properties sign candidate articulation point; And the joint coupling is to extract skeleton structure from the exercise data file, recovers skeleton, mates with candidate's articulation point then.In current skeletal extraction and the joint matching process, " matching virtual human model and the exercise data automatically " that Hu Xiaoyan delivers at 2006 " Journal of Software " proposed section sign candidate articulation point, and the method for candidate's articulation point being carried out semantic analysis.Also has " subjoint of closed polygon model " (Teichmann M that Plutarch is graceful and Taylor delivered in " computer animation and emulation " in 1998, Teller S.Assisted articulation of closed polygonal models.In ComputerAnimatio and Simulation, 1998[C], Lisbon, Portugal:European Association for ComputerGraphics, 1998:87-101.) method of Wei Nuo (Voronoi) skeleton that proposes, but these methods all more or less need user interactions, can not realize whole leaching process robotization.
In the skin deformation method, in skin. " the linear invariable rotary coordinate system of grid model " that Yanaon was delivered at " ACM figure journal " in 2005 (Yaron Lip.Linear rotation invariant coordinates for meshes[j], ACM Transactions on Graphics 2005,24,479-487.) and " using the Poisson editor's grid based on gradient field control " (Yizhou Yu etc of delivering at " ACM figure journal " in 2004 of people such as Yu Yizhou, Mesh editing with poisson basedgradient field manipulation[j], ACM Transactions on Graphics, 2004,23,3 (Aug.), 644-651.) skin deformation based on model surface that proposes, " using body figure Laplace transform to realize macroreticular distortion " (Kun Zhou that Zhou Kun delivered at " ACM figure journal " in 2005,2005.Large mesh deformation using thevolumetric graph laplacian.ACM Transaction on Graphics 24,3 (Aug), 496-503.) skin deformation based on entity that proposes is two kinds of relatively classic methods, the skin deformation based on entity of proposition is two kinds of relatively classic methods.But these methods spy needs manual interaction to set bone position and weight, can not realize the robotization of weight allocation process.
Summary of the invention
All need manual intervention in order to overcome prior art, can not realize the deficiency of robotization, the invention provides a kind of full-automatic driving method of three-dimensional motion model based on three-dimensional motion parameter, can finish that the model skeleton automatically extracts and mate automatically in the joint, the automatic distribution of skin weight, thus the automatic driving of realization three-dimensional motion model.
The technical solution adopted for the present invention to solve the technical problems may further comprise the steps:
The first step at first reads the movable information file, recovers exercise data, obtains initial bone template.
What store in the movable information file is performance people's bone joint information, common move file has: BVH, AMC/ASF, BVA or the like, with the BVH file is example, the BVH file divides the data of skeletal structure and movable information two aspects, has defined the initial displacement and the corresponding inheritance of bone in the skeletal structure with tree structure, and movable information has then been preserved the rotation angle in the joint of the every frame of each bone.We can obtain initial bone template from skeletal structure, initial bone template has only defined initial displacement and bone tree structure, does not have rotation information, is used for next step skeleton coupling, from movable information, can obtain the exercise data in each joint, be used for last driving model motion.
Second step, to the given model of user, carry out skeleton line and extract, and mark candidate articulation point.Step is as follows:
Step1: voxelization model at first makes up distance map.
Step2: use shortest path first (Dijkstra) obtains the minimum-weight path between any two voxels; From model top voxel,, in the transition skeletal tree, finish with loop iteration algorithm interpolation voxel farthest up to all voxel interpolations, skeletal tree generates.
Step3: the skeletal tree of generation, the quantity of point is too much, is unfavorable for that we mate.So we adopt the method for receiving in adding to filter some inappropriate points to the skeletal tree that generates: earlier the point on the skeletal tree according to put model surface apart from descending sort.From first sampled point, be the centre of sphere with this point, the distance of putting model surface is a radius, add a ball, order is carried out, if this point is in the ball that certain had added, do not add ball so, continue next sampled point according to the order of sequence, carry out till the last point.The ball that is to say the radius maximum is added at first, and each ball inside does not comprise the centre of sphere of other balls.Finish receive in the interpolation after, we are made as candidate's articulation point to the interior centre of sphere of receiving.
Step4: for the point after filtering, be to classify to candidate's articulation point in the center with the body central shaft, be divided into: two points near model bottom, the some centre of sphere near a model top and a big ball, are used for the automatic coupling in the 3rd step about body central shaft symmetry, point.
In the 3rd step, mate the corresponding joint point automatically.
Initial bone template is zoomed to model skeleton line ratio, utilize the classification results in second step and the positional information of candidate's articulation point to set the corresponding constraint of judging.
(1) being labeled as the joint of pin will be in model bottom.Be labeled as the joint of pin for each, decision content is poor for the y coordinate of the point of y coordinate minimum in all summits of the y coordinate of point of coupling and bone template.
(2) degree is that 1 articulation point should be far away apart from father node, and its criterion is that 1 articulation point matches a v for this degree
2, its father node matches a v
1(be different from a v
2), if vertex v
3Adjacent to a v
2, and it in the radius of receiving be 1/2 of the radius of receiving in the v2 at least, decision content is 1 so.
(3) length can not be arranged is 0 skeletal chain, and promptly joint and its father node can not be same node by coupling.As be not inconsistent, decision content is 1.
(4) the corresponding bone section ratio of bone after the coupling and original bone template should be suitable.
(5) be labeled as symmetrical bone, also should symmetry after the coupling.
Define each and judge the corresponding decision function of constraint, each decision function all has corresponding weights, if violated the decision content that certain agreement must its decision function, seeks the optimum solution that is of all articulation point decision content addition minimums of skeletons coupling combination.In candidate's articulation point, seek the most similar skeleton coupling.
The 4th step, carry out the automatic binding of bone and skin, finish the distribution of skin summit bone weight.
Utilize the simulate thermal equilibrium effect to distribute the bone weight: the distribution of simulation heat temperature in body space inside assigns weight, model is seen as a heat conductor, if bone i, heating bone i, make its temperature be raised to 1, keeping other bone temperature simultaneously is 0, after thermal equilibrium, we in the equilibrium temperature on this lip-deep summit as the weight of bone i on this summit.Balance equation is as follows:
-Δw
i+Hw
i＝Hp
i
Δ is the discrete surface Laplace operator, and w represents the weight of bone, p
iBe a vector, if the nearest bone of summit j is i,
Otherwise
H is a diagonal matrix, H
IjBe the hot weights of summit j to nearest bone.If d (j) is the distance of summit j to nearest bone, generally use H
Jj=C/d (j)
2, C is the bone sum; After definite equation factor, with H
JjSubstitution obtains the weight of each bone.Be updated to then in the LBS algorithmic formula:
Make V
jRepresent the coordinate of summit j, T
iBe the transformation matrix of i bone, and W
JiBe the weight of i bone for summit j, B so
jBe the new coordinate after the j conversion of summit, load exercise data and upgrade the skin apex coordinate, realize skin deformation.
The invention has the beneficial effects as follows: in move file, extract the bone template owing to adopted, make the manual setting of no longer choosing of bone template, owing to adopted the extraction skeletal tree, the mark candidate articulation point, make the bone template can in a certain amount of candidate's articulation point, seek optimum coupling, the effect that has guaranteed automatic extraction and coupling also has the time of carrying out, owing to adopted improved lBS algorithm, can be under the prerequisite that guarantees real-time, automatically finish the distribution of bone weight, guaranteed whole skeletal extraction, coupling, the finishing automatically of anamorphotic system.Full-automatic driving method of three-dimensional motion model based on three-dimensional motion parameter of the present invention does not need man-machine interactively, do not need the professional, the user only need read model file, just can finish the extraction and the coupling of bone automatically, the binding of skin, thereby the driving of implementation model.Whole driving setup time generally 1 minute with interior (decision of perceived model scale), this be traditional driving model method can not compare, it has saved the time of model-driven greatly, has saved manpower, material resources.If be used for media production, can improve media production efficient greatly.
The present invention is further described below in conjunction with drawings and Examples.
Description of drawings
Fig. 1 is a process flow diagram of the present invention.
Embodiment
Method embodiment: instance model does not contain bone information.
Experiment hardware environment: inte1 core2 e6300 (1.86G)+IG internal memory.
Experiment software environment: VS2005+Openg1.
The first step reads the bvh file earlier, and the example move file contains the information of 18 bones, and 329 frame exercise datas are arranged, and is initial bone template with the bone information extraction.Read instance model, the file of instance model has 39kb, contains 1033 summits, 6186 limits.
Second one, adopt the wade method to make up distance map, voxel size 0.02, finish and to form corresponding distance relation between the voxel of model inside, we are with the voxel of the peak of model, as the initial voxel point of skeletal tree, we use dijkstra's algorithm to calculate minimum-weight path between any two voxels; , finish up to all voxel interpolations in skeletal tree with loop iteration algorithm interpolation voxel farthest, skeletal tree generates.The skeletal tree of model 1 contains 4547 points, the point of the skeletal tree that generates distributes near model inside center line, it is more to count, be unfavorable for directly mating, so use inner method of adding ball, filter a part of point, earlier the point on the skeletal tree according to put model surface apart from descending sort.From first sampled point, if this point is in the outside of all balls that added, be the centre of sphere with this point so, point is a radius to the distance of model surface, add a ball, if this in certain ball, does not add ball so, continue next sampled point according to the order of sequence, carry out till the last point.The ball that is to say the radius maximum is added at first, and each ball inside does not comprise the centre of sphere of other balls.Finish receive in the interpolation after, we are made as candidate's articulation point counting after adding ball and filtering to the interior centre of sphere of receiving is 137, we are divided into 4 classes with these 137 points,
(1) if two points about model center line symmetry, then two points are labeled as one group of symmetric points.
(2) as fruit dot in model bottom, then be labeled as feet.
(3) as fruit dot at the model top, then be labeled as head.
(4) be the centre of sphere of a big ball as fruit dot, then be labeled as bigsphere.
The 3rd step zoomed to model skeleton line ratio with initial bone template, utilized the classification results of previous step and the positional information of candidate's articulation point.Set the corresponding constraint of judging, and the definition decision function,
(1) being labeled as the joint of feet will be in model bottom.Be labeled as the joint of pin for each, decision content is poor for the some y coordinate of all summit y coordinate minimums among the coordinate of point of coupling and the figure.
(2) degree is that 1 articulation point should be far away apart from father node, matches v if degree of very near hypothesis is 1 articulation point
2, its father node matches v
1(be different from v
2), if vertex v
3Adjacent to v
2, and its radius of a ball is 1/2 of the v2 radius of a ball at least, decision content is 1 so.
(3) length can not be arranged is 0 skeletal chain, and promptly joint and its father node can not be same node by coupling.As be not inconsistent, decision content is 1.
(4) the corresponding bone section ratio of bone after the coupling and original bone template should be suitable.
(5) be labeled as symmetrical bone, also should symmetry after the coupling.
These each decision functions of constraint with geometric meaning all have corresponding weights (0.15,0.27,0.24,0.3,0.65), if violated the decision content that certain agreement must its decision function, seek all skeletons coupling all articulation point decision contents of combination and weight long-pending addition minimum be optimum solution.When beginning to find the solution problem, directly using the method that minimizes decision function to find the solution problem is the comparison difficulty, because the possibility of finding the solution is exponential, consider that progressive method simplifies the form of finding the solution, if we mate the sub-fraction (perhaps indivedual several articulation points) of skeleton earlier, add the articulation point of closing on then gradually, form a progressive matching process, this is feasible.Generally speaking, the articulation point that in-degree is high should be mated earlier, because the high node of in-degree is big for the skeletal structure entire effect, and after it determines, can further determine to form its branch accurately and mate.
Specific practice is: the coupling to each articulation point of standard form is successively done an ordering, and order standard is: (1) in-degree from big to small.(2) added one deck in-degree node after, the child node of adding them is also arranged by in-degree size.If a formation is earlier joined the team the ground floor node, calculate local Optimum Matching, add ingress more gradually, node of every adding all will calculate the coupling of local optimum.Finish up to all nodes addings, all nodes go out team, get matching result to the end.
In the 4th step, we assigned weight according to the position of surface point to corresponding joint after the skeleton coupling was finished, and the distribution of weight adopts the method for finding the solution thermal balance equation to find the solution
Thermal balance equation is as follows:
-Δw
i+Hw
i＝Hp
i
Δ is the discrete surface Laplace operator, can be by Meyer
[8]Calculate.p
iBe a vector, if the nearest bone of summit j is i,
Otherwise
H is a diagonal matrix H
IjBe the hot weights of summit j to nearest bone.If d (j) is the distance of summit j to nearest bone, use H in the experiment
Jj=C/d (j)
2, C=0.2, the substitution parameter obtains the weights W of each bone.Be updated to then in the LBS algorithmic formula:
Make V
jRepresent the coordinate of summit j, T
iBe the transformation matrix of i bone, can obtain by exercise data, and W
JiBe the weight of i bone for summit j, B so
jBe the new coordinate after the j conversion of summit, load exercise data, obtain the move T of different bones of every frame, the skin apex coordinate after the substitution formula can obtain being out of shape is realized skin deformation.The execution time following (ms) of whole driving preparatory stage various piece algorithm:
| Make up the distance domain time | 4547? |
| The time of coupling | 1578? |
| The time of skin binding | 62? |
| T.T. | 9984? |
In whole extraction time, it is relevant with the model scale to make up the distance domain time, and it is longer to occupy the time, and the time of coupling is relevant with the skeleton diagram complexity that constitutes, and the time differs.Extract sampled point, add ball, design of graphics, the model scale is irrelevant more fixing, and it is shorter to occupy the time, and the time of skin binding is relevant with the model vertices number, and the time decides according to the number of vertex size, and the whole time is in one minute.
Claims (1)
1. based on the full-automatic driving method of three-dimensional motion model of three-dimensional motion parameter, it is characterized in that comprising the steps:
(a) read the movable information file, recover exercise data, obtain initial bone template;
(b) the bone template that previous step is obtained is carried out the skeleton line extraction, and mark candidate articulation point, comprises the steps:
(1) voxelization model makes up distance map;
(2) the improved shortest path first of use obtains the minimum-weight path between any two voxels; , finish up to all voxel interpolations in skeletal tree with loop iteration algorithm interpolation voxel farthest, skeletal tree generates;
(3) the point on the skeletal tree according to put model surface apart from descending sort, from first sampled point, with this point is the centre of sphere, and the distance of putting model surface is a radius, adds a ball, order is carried out, if this point in the ball that certain had added, does not add ball so, continue next sampled point according to the order of sequence, carry out till the last point, in the centre of sphere of receiving be made as candidate's articulation point;
(4) be to classify to candidate's articulation point in the center with the body central shaft;
(c) mate the corresponding joint point automatically, comprise the steps:
(1) joint that is labeled as pin will be labeled as the joint of pin for each in model bottom, and decision content is poor for the y coordinate of the point of y coordinate minimum in all summits of the y coordinate of the point of coupling and bone template;
(2) degree is that 1 articulation point should be far away apart from father node, and its criterion is that 1 articulation point matches a v for this degree
2, its father node matches a v
1If, vertex v
3Adjacent to a v
2, and it in the radius of receiving be 1/2 of the radius of receiving in the v2 at least, decision content is 1 so;
(3) length can not be arranged is 0 skeletal chain, and promptly joint and its father node can not be same node by coupling; As be not inconsistent, decision content is 1;
(4) the corresponding bone section ratio of bone after the coupling and original bone template should be suitable;
(5) be labeled as symmetrical bone, also should be symmetrical after the coupling;
(d) carry out the automatic binding of bone and skin, finish the distribution of skin summit bone weight, comprise the steps:
Utilize the simulate thermal equilibrium effect to distribute the bone weight: the distribution of simulation heat temperature in body space inside assigns weight, model is seen as an adiabatic conductor, if bone i, heating bone i, make its temperature be raised to 1, keeping other bone temperature simultaneously is 0, after thermal equilibrium, we in the equilibrium temperature on this lip-deep summit as the weight of bone i on this summit, balance equation is as follows :-Δ w
i+ Hw
i=Hp
i, Δ is the discrete surface Laplace operator, w represents the weight of bone, p
iBe a vector, if the nearest bone of summit j is i,
Otherwise
H is a diagonal matrix, H
IjBe the hot weights of summit j to nearest bone; If d (j) is the distance of summit j to nearest bone, generally use H
Ij=C/d (j)
2, C is the bone sum; With H
JjBe updated in the formula:
Make V
jRepresent the coordinate of summit j, T
iBe the transformation matrix of i bone, and W
JiBe the weight of i bone for summit j, B so
jBe the new coordinate after the j conversion of summit, load exercise data and upgrade the skin apex coordinate, realize skin deformation.
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| CN103606178A (en) * | 2013-10-23 | 2014-02-26 | 合肥工业大学 | Interactive motion data acquisition method based on portable terminal |
| CN104658022B (en) * | 2013-11-20 | 2019-02-26 | 中国电信股份有限公司 | Three-dimensional animation manufacturing method and device |
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| CN105551073B (en) * | 2015-12-30 | 2018-08-03 | 东北大学 | A kind of bone binding method of three-dimensional (3 D) manikin |
| CN107491506B (en) * | 2017-07-31 | 2020-06-16 | 西安蒜泥电子科技有限责任公司 | Batch model posture transformation method |
| CN108320326A (en) * | 2018-01-12 | 2018-07-24 | 东南大学 | A kind of three-dimensional modeling method for human hand |
| CN109215128B (en) * | 2018-08-09 | 2019-12-24 | 北京华捷艾米科技有限公司 | Object motion attitude image synthesis method and system |
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