Download An Application of Lie theory to Computer Graphics

An Application of Lie theory
to Computer Graphics
Applied Topology
25th July. 2013. Będlewo
Shizuo KAJI
Yamaguchi University
JST/CREST
Outline
Blend Shape
- a problem in CG
Mathematical setup
Our solution
Blend Shape
Japanese ex-prime
Statue ofminister
Moai Mori
Blend Shape – The problem
Problem:
From (two or more) input images, generate interpolated images
input: A, B => “(1-t)A + tB”: output
Input
Output
t=0.5
Where is it used ?
•
•
•
•
•
Michael Jackson “Black or White”
Movie: Terminator 2、Forest Gump…
Creating new industrial design
Video compression, High framerate TV
Adobe Photoshop/After effects Puppet Warp
Igarashi et al. 2005
Beier and Neely 1992
Blend Shape – basic idea
input: A, B => “(1-t)A + tB”: output
Construct a series of homeos indexed by t ∈ R
ft : R2 → R2 t ∈ R
It usually requires additional input
which should be given manually.
(ex. the arrows in the picture)
Weakness of classical method
desirable
What is an
appropriate setup
for this problem ?
Simplicial complex
In CG, the most basic representation of geometric object is
(triangulated) polyhedron, i.e., simplicial complex
2D
3D
Simplicial complex
More precisely,
・Abstract simplicial complex
(= set of tetrahedra)
・Piecewise Linear (PL) embedding
(= vertex positions in Rn)
Paraphrase of blend shape
Instead of considering objects themselves,
・Consider embeddings from a (reference) simplicial complex
・And find a “suitable” path in the space of embeddings
fA/2+B/2
Our algorithm
Based on Joint works with
K. Anjyo, S. Hirose, H. Ochiai
and
K. Anjyo, S. Hirose, Y. Mizoguchi, S.Sakata
Workflow
Problem
From given input shapes, generate interpolated shapes
input: A, B => “(1-t)A + tB”: output
Our strategy is divided into three steps
1. Express input shapes by PL-maps from
a reference simplicial complex
For each t ∈ R;
2. Construct interpolated affine maps
independently for each simplex
3. Assemble those maps into a global PL-immersion
1. Isomorphic subdivision
Sub problem
Given homeomorphic simplicial complexes,
subdivided them to make combinatorially isomorphic
Fact: Homeo  PL-isomorphic (dimension≦3)
There are algorithms to give an explicit isomorphism.
But none of them is perfect.
This is still an open problem in computational geometry.
1-to-1
We simply rely on existing methods here
Assume we have PL-embeddings fA, fB of a reference simplicial complex
to the shapes to be blended.
We want to find a homotopy Ht connecting fA and fB.
H1/2
Ht
2. Local construction
First, we consider simplex-wisely
Sub problem
For each simplex,
construct a time varying series of
interpolated affine maps,
which preserve geometry locally.
2. Local construction
More precisely,
Sub problem
Given two affine maps X and Y,
generate a blended affine map At := “(1-t)X + tY”
The first guess for the answer would be simply the linear
combination of X and Y, but it produces bad results.
undesirable
desirable
2. Local construction
The second guess would be using Lie correspondence
Lie algebra
Lie group
But the problem is the group of affine transformations is not compact.
Based on the Cartan decomposition, we have the following surjection,
which meets our need.
The above map is almost bijective and its continuous inverse ψ can be computed.
2. Local construction
Now we can blend affine maps linearly in the parameter space
Key points:
・
is not surjective
・There is an explicit and fast computation algorithm for φ, ψ
・The blended map has geometric meaning:
for example, the interpolated map stays as close as
Euclidean motion (In the sense of Frobenius norm)
Nice both geometrically and computationally !
3. Patching local maps
Local
to
Global
Sub problem
Assemble the locally constructed
affine maps into a global PL-map
It is done by finding the minimum of a certain
energy functional on the space of PL-immersions.
The energy functional
: the simplex-wisely blended affine map
Key points:
* It measures the difference between the PL-map and the locally
constructed maps up to PL-conformal equivalence
* The minimizer is unique (modulo linear conformal equivalence)
and varies smoothly with regard to t
 Invariant under conformal transformation
 Users can easily direct the result by adding some terms to it
Visual consequence
Trajectory of a point
Is specified by user
Energy w/o
invariance
Energy w/
invariance
Left and center: user defined constraints
Right: effect of PL-conformal invariance
Applications
Our algorithm directly generalizes to more than two inputs
input: A, B, C, D… => “sA + tB + uC + vD + …”: output
Furthermore, nice properties of our linear parametrization of the
affine transformation group allow various applications
・shape deformer
(addition/scalar product)
・Inverse kinematics (calculus/differential equation)
・Motion analysis/compression using PCA/ICA (linear algebra)
Demo
Three shapes are blended according to weights.
Weights are specified by user through the “ball controller”
Demo
Target shape (dino) is deformed according to user’s operation on
the yellow cage.
Demo
Shapes are deformed according to
user manipulated handles (invisible)
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There will be a conference on “Math for CG” in October
Google “MEIS2013” for detail