Game Development Reference
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Hence, after computing Equation (10.20), we obtain
T 2 , 2 ,T 2 , 3 ,T 2 , 4
T 3 , 2 ,T 3 , 3 ,T 3 , 4
T 4 , 2 ,T 4 , 3 ,T 4 , 4
,
F =
(10.21)
where T i,j are the matrix T elements and i, j
.
This technique requires storing P e (see Equation (10.19)), i.e., 16 floating-
point numbers. Storing this matrix is useful when we have a detailed surface mesh
driven by the tetrahedral mesh, as we will show in Section 10.5.
Alternatively, we can compute the gradient F using the following, less-
memory-consuming technique, which requires only nine floats per element.
Let the matrix D e of an element e be
∈{
1 , 2 , 3 , 4
}
p 1 ,x
p 4 ,x
p 2 ,x
p 4 ,x
p 3 ,x
p 4 ,x
,
D e =
p 1 ,y
p 4 ,y
p 2 ,y
p 4 ,y
p 3 ,y
p 4 ,y
p 1 ,z
p 4 ,z
p 2 ,z
p 4 ,z
p 3 ,z
p 4 ,z
where its elements are made by the element e nodes in their rest positions. Simi-
larly, we can build G e using the nodes of the tetrahedron e in its deformed posi-
tion. Hence, the deformation gradient of the tetrahedron e can be defined as
F = G e D e .
Note that G e changes in every iteration but D e remains constant, so it can be
precomputed and stored using nine floating-point numbers.
Once we have computed F , we can extract the rotation using a polar decompo-
sition technique. The polar decomposition technique factorizes F in two matrices:
a rotation R and a positive definite symmetric matrix U . The polar decomposi-
tion computes the nearest unitary basis to the column axes. This ensures that the
U contains the smallest deformation. The method initially computes U 2 as FF T .
Then we compute U as
U = U 2 = λ 1 v 1 ·
+ λ 2 v 2 ·
+ λ 3 v 3 ·
v 1
v 2
v 3 ,
are the eigenvectors of U 2 and
where
{
v 1 ,v 2 ,v 3 }
{
λ 1 2 3 }
are its associated
eigenvalues. Both
can be calculated using the Jacobi
transformations of a symmetric matrix. Describing this method is outside the
scope of this chapter, but the reader can refer to [Press et al. 07] for sample code
and further information. Finally, we can compute the tetrahedron rotation R from
R = FU 1 .
{
v 1 ,v 2 ,v 3 }
and
{
λ 1 2 3 }
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