Animation of 3D surfaces

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Transcription:

Animation of 3D surfaces 2013-14

Motivations When character animation is controlled by skeleton set of hierarchical joints joints oriented by rotations the character shape still needs to be visible: visible = to be rendered as a continuous shape typically, a surface is rendered 2

Motivations visible shape is made of organic tissues 3

Motivations visible shape is made of organic tissues 4

Motivations What is the goal of 3D animation? 5

Motivations 3D animation workflow 6

Motivations Animation of 3D surface is actually the most practical thing: direct connection with modeling phase shape and texture light structure, easy to animate possibly real-time works will be focused on workarounds to cope with this approximation of reality 7

Overview Skinning Non-linear deformers Shape morphing Mesh edition 8

Overview Skinning Non-linear deformers Shape morphing Mesh edition 9

Skinning Goal: bind a skeleton and a shape P 1 P P P 2 10

Skinning Linear blend skinning P P2 P P1 P = w1*p1 + w2*p2 11

Skinning Linear blend skinning B A P Q B A P2 Q P1 P P = w 1 *P1 + w 2 *P2 w i : [0..1], skin weights 12

Skinning Linear blend skinning M 2 (θ) P 0 P 2 P 1 P θ M 0,1 M 0,2 M 1 P = w 1 *P 1 + w 2 *P 2 M : R and T with P i = M 0,i M i (θ)m -1 0,i P 0 13

Skinning Linear blend skinning A P 0 Q 0 B A Q B M 2 (θ) P θ M 0,1 M 0,2 M 1 P = Σ i w i * M 0,i M i (θ)m -1 0,i P 0 Implemented as Skin>Smooth bind in Maya 14

Skinning Linear blend skinning B A P B A P(θ) δ δ λ Q λ θ Q(θ) 15

Skinning Limitations P = Σ i w i * M 0,i M i M -1 0,i P 0 = ( Σ i w i * M 0,i M i M -1 0,i ) P 0 Non-rigid transformation 16

Skinning Improvements Skinning as a prediction function from joint configuration to 3D shapes V = f a (θ) = Σ i a i f( θ -θ i ) [ θ n, V n ] θ in R m, with m joints dof V in R p, with p mesh vertices a i in R p, n parameters [ θ 1, V 1 ] [Lewis et al., 2000] [ θ i, V i ] a = argmin Σ i V i f a (θ i ) 2 f a (θ) = Σ i a i f( θ -θ i ) Radial Basis Function (RBF) 17

Skinning Improvements Incorporate user-defined examples of shapes and automatically add some joints and weights in LBS [Mohr et Gleicher, 2003] 18

Skinning Improvements Compute the matrix interpolation while maintaining correct rotations, using dual quaternions P = Σ i w i * M 0,i M i M -1 0,i P 0 = ( Σ i w i * M 0,i M i M -1 0,i ) P 0 [Kavan et al., 2007] 19

Overview Skinning Non-linear deformers Shape morphing Mesh edition 20

Non-linear deformers Global modification of 3D shapes the transformation matrix is a function of R 3 point 21

Non-linear deformers Non-uniform rotation (twisting) 22

Non-linear deformers Vortex 23

Non-linear deformers Free-Form Deformation (FFD) Object embedded in 3D rubber 24

Non-linear deformers FFD : Space interpolation 25

Non-linear deformers FFD applications to non-characters objects 26

Non-linear deformers Preserving volume V = 4/3 π abc b = ¾ V / ( π ac) Influence object combined with skinning [Scheepers et al., 97] 27

Non-linear deformers Preserving volume Motion of Muscles induces a displacement field [Angelidis et Singh, 2007] 28

Overview Skinning Non-linear deformers Shape morphing Mesh edition 29

Shape blending a 3D shape is a linear combination of reference shapes a linear interpolation for each vertex, S = S 0 +Σ i w i (S i -S 0 ) animation is controlled by blend coefficient w i typical application is facial animation 30

Shape blending Blend Shapes 31

Shape blending Facial animation : two main domains Emotion any expression is combination of basic expression: fear, disgust, joy, surprise, anger [Ekman, 75] Talking visual perception of speech production 32

Lip-synching Difficult task how to post-synchronized video onto audio track one common solution : a phoneme = a 3D shape several visually equivalent phonemes as a viseme [p,b,m], [f,v], etc. 33

Lip-synching Problem of the co-articulation effect audio-visual speech signal is continuous audio and visual are not synchronized by nature (anticipation and latency) gesture vs shape [Reveret et Essa, 2001] 34

Overview Skinning Non-linear deformers Shape morphing Mesh edition 35

Barycentric coordinates Low-resolution «cage» controlling a highresolution mesh each vertex is a linear combination w.r.t cage vertices and normals => local coordinates or weights difficulty: getting the right weights, leading to little artefacts Mean value coordinates, Harmonic coordinates, Green coordinates, etc 36

Laplacian mesh edition Character animation without a skeleton Group of vertices are locally deformed while preserving surface details Based on discrete differential geometry [Sorkine et al., 2004] 37

Laplacian mesh edition Each vertex coordinate is replaced by the difference to the average of its neighbors D = L V : d i = V i -(1/ N i )Σ kϵni V k Deformation by adding constrains add some rows to L => L* and D => D* Reconstruction of V by approximation V* = argmin V ( L V D ) More details on: http://igl.ethz.ch/projects/laplacian-mesh-processing/star/star- Laplacian-mesh-processing.pdf 38

Laplacian mesh edition Application to key-frame animation [Xu et al., 2006] 39