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This commit is contained in:
OpenCV Buildbot
2012-10-17 11:12:04 +04:00
committed by Andrey Kamaev
parent 0442bca235
commit 81f826db2b
1511 changed files with 258678 additions and 258624 deletions
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78
3rdparty/openexr/Imath/ImathMatrixAlgo.cpp vendored
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@@ -2,9 +2,9 @@
//
// Copyright (c) 2002, Industrial Light & Magic, a division of Lucas
// Digital Ltd. LLC
//
//
// All rights reserved.
//
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
@@ -16,8 +16,8 @@
// distribution.
// * Neither the name of Industrial Light & Magic nor the names of
// its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
//
// from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
@@ -54,22 +54,22 @@
namespace Imath {
EXPORT_CONST M33f identity33f ( 1, 0, 0,
0, 1, 0,
0, 0, 1);
0, 1, 0,
0, 0, 1);
EXPORT_CONST M33d identity33d ( 1, 0, 0,
0, 1, 0,
0, 0, 1);
0, 1, 0,
0, 0, 1);
EXPORT_CONST M44f identity44f ( 1, 0, 0, 0,
0, 1, 0, 0,
0, 0, 1, 0,
0, 0, 0, 1);
0, 1, 0, 0,
0, 0, 1, 0,
0, 0, 0, 1);
EXPORT_CONST M44d identity44d ( 1, 0, 0, 0,
0, 1, 0, 0,
0, 0, 1, 0,
0, 0, 0, 1);
0, 1, 0, 0,
0, 0, 1, 0,
0, 0, 0, 1);
namespace
{
@@ -175,10 +175,10 @@ procrustesRotationAndTranslation (const Vec3<T>* A, const Vec3<T>* B, const T* w
if (doScale && numPoints > 1)
{
// Finding a uniform scale: let us assume the Q is completely fixed
// at this point (solving for both simultaneously seems much harder).
// at this point (solving for both simultaneously seems much harder).
// We are trying to compute (again, per Golub and van Loan)
// min || s*A*Q - B ||_F
// Notice that we've jammed a uniform scale in front of the Q.
// Notice that we've jammed a uniform scale in front of the Q.
// Now, the Frobenius norm (the least squares norm over matrices)
// has the neat property that it is equivalent to minimizing the trace
// of M^T*M (see your friendly neighborhood linear algebra text for a
@@ -231,7 +231,7 @@ procrustesRotationAndTranslation (const Vec3<T>* A, const Vec3<T>* B, const T* w
// [ 0 1 0 tb ] [ s*Q 0 ] [ 0 1 0 -ta ] = [ 0 1 0 tb ] [ s*Q -s*Q*ta ] = [ Q tb-s*Q*ta ]
// [ 0 0 1 | ] [ 0 ] [ 0 0 1 | ] [ 0 0 1 | ] [ | ] [ ]
// [ 0 0 0 1 ] [ 0 0 0 1 ] [ 0 0 0 1 ] [ 0 0 0 1 ] [ 0 0 0 1 ] [ 0 0 0 1 ]
// (ofc the whole thing is transposed for Imath).
// (ofc the whole thing is transposed for Imath).
const V3d translate = Bcenter - s*Acenter*Qt;
return M44d (s*Qt.x[0][0], s*Qt.x[0][1], s*Qt.x[0][2], T(0),
@@ -265,7 +265,7 @@ namespace
// J * A
// for the Jacobi rotation J and the matrix A. This is efficient because we
// only need to touch exactly the 2 columns that are affected, so we never
// need to explicitly construct the J matrix.
// need to explicitly construct the J matrix.
template <typename T, int j, int k>
void
jacobiRotateRight (Imath::Matrix33<T>& A,
@@ -312,7 +312,7 @@ jacobiRotateRight (Imath::Matrix44<T>& A,
// 'Computation of the Singular Value Decomposition using Mesh-Connected Processors'
// by Richard P. Brent, Franklin T. Luk, and Charles Van Loan
// It breaks the computation into two steps: the first symmetrizes the matrix,
// and the second diagonalizes the symmetric matrix.
// and the second diagonalizes the symmetric matrix.
template <typename T, int j, int k, int l>
bool
twoSidedJacobiRotation (Imath::Matrix33<T>& A,
@@ -402,7 +402,7 @@ twoSidedJacobiRotation (Imath::Matrix33<T>& A,
const T d_2 = s_1*(w*s_2 + x*c_2) + c_1*(y*s_2 + z*c_2);
// For the entries we just zeroed out, we'll just set them to 0, since
// they should be 0 up to machine precision.
// they should be 0 up to machine precision.
A[j][j] = d_1;
A[k][k] = d_2;
A[k][j] = 0;
@@ -415,7 +415,7 @@ twoSidedJacobiRotation (Imath::Matrix33<T>& A,
// [ -s1 c1 0 ] or [ 0 1 0 ] or [ 0 c1 s1 ]
// [ 0 0 1 ] [ -s1 0 c1 ] [ 0 -s1 c1 ]
// This has the effect of adding the (weighted) ith and jth _rows_ to
// each other.
// each other.
const T tau1 = A[j][l];
const T tau2 = A[k][l];
A[j][l] = c_1 * tau1 - s_1 * tau2;
@@ -428,7 +428,7 @@ twoSidedJacobiRotation (Imath::Matrix33<T>& A,
// [ -s2 c2 0 ] or [ 0 1 0 ] or [ 0 c2 s2 ]
// [ 0 0 1 ] [ -s2 0 c2 ] [ 0 -s2 c2 ]
// This has the effect of adding the (weighted) ith and jth _columns_ to
// each other.
// each other.
const T tau1 = A[l][j];
const T tau2 = A[l][k];
A[l][j] = c_2 * tau1 - s_2 * tau2;
@@ -436,7 +436,7 @@ twoSidedJacobiRotation (Imath::Matrix33<T>& A,
}
// Now apply the rotations to U and V:
// Remember that we have
// Remember that we have
// R1^T * A * R2 = D
// This is in the 2x2 case, but after doing a bunch of these
// we will get something like this for the 3x3 case:
@@ -543,7 +543,7 @@ twoSidedJacobiRotation (Imath::Matrix44<T>& A,
const T d_2 = s_1*(w*s_2 + x*c_2) + c_1*(y*s_2 + z*c_2);
// For the entries we just zeroed out, we'll just set them to 0, since
// they should be 0 up to machine precision.
// they should be 0 up to machine precision.
A[j][j] = d_1;
A[k][k] = d_2;
A[k][j] = 0;
@@ -566,7 +566,7 @@ twoSidedJacobiRotation (Imath::Matrix44<T>& A,
// j k
//
// This has the effect of adding the (weighted) ith and jth _rows_ to
// each other.
// each other.
const T tau1 = A[j][l];
const T tau2 = A[k][l];
A[j][l] = c_1 * tau1 - s_1 * tau2;
@@ -590,7 +590,7 @@ twoSidedJacobiRotation (Imath::Matrix44<T>& A,
// j k
//
// This has the effect of adding the (weighted) ith and jth _columns_ to
// each other.
// each other.
const T tau1 = A[l][j];
const T tau2 = A[l][k];
A[l][j] = c_2 * tau1 - s_2 * tau2;
@@ -598,7 +598,7 @@ twoSidedJacobiRotation (Imath::Matrix44<T>& A,
}
// Now apply the rotations to U and V:
// Remember that we have
// Remember that we have
// R1^T * A * R2 = D
// This is in the 2x2 case, but after doing a bunch of these
// we will get something like this for the 3x3 case:
@@ -679,7 +679,7 @@ twoSidedJacobiSVD (Imath::Matrix33<T> A,
// [-s1 c1 ] [ * *] [-s2 c2 ] = [* * *]
// [ 1] [* * *] [ 1] [ * *]
// However, if we keep doing this, we'll find that the off-diagonal entries
// converge to 0 fairly quickly (convergence should be roughly cubic). The
// converge to 0 fairly quickly (convergence should be roughly cubic). The
// result is a diagonal A matrix and a bunch of orthogonal transforms:
// [* * *] [* ]
// L1 L2 ... Ln [* * *] Rn ... R2 R1 = [ * ]
@@ -690,7 +690,7 @@ twoSidedJacobiSVD (Imath::Matrix33<T> A,
// are extremely stable to compute and apply (this is why QR factorization
// works so well, FWIW) and because (2) by applying everything to the original
// matrix A instead of computing (A^T * A) we avoid any precision loss that
// would result from that.
// would result from that.
U.makeIdentity();
V.makeIdentity();
@@ -769,7 +769,7 @@ twoSidedJacobiSVD (Imath::Matrix33<T> A,
U[i][2] = -U[i][2];
S.z = -S.z;
}
if (V.determinant() < 0)
{
for (int i = 0; i < 3; ++i)
@@ -881,7 +881,7 @@ twoSidedJacobiSVD (Imath::Matrix44<T> A,
U[i][3] = -U[i][3];
S[3] = -S[3];
}
if (V.determinant() < 0)
{
for (int i = 0; i < 4; ++i)
@@ -946,7 +946,7 @@ namespace
{
template <int j, int k, typename TM>
inline
inline
void
jacobiRotateRight (TM& A,
const typename TM::BaseType s,
@@ -1005,7 +1005,7 @@ jacobiRotation (Matrix33<T>& A,
A[k][k] += h;
// For the entries we just zeroed out, we'll just set them to 0, since
// they should be 0 up to machine precision.
// they should be 0 up to machine precision.
A[j][k] = 0;
// We only update upper triagnular elements of A, since
@@ -1015,7 +1015,7 @@ jacobiRotation (Matrix33<T>& A,
const T nu1 = offd1;
const T nu2 = offd2;
offd1 = nu1 - s * (nu2 + tau * nu1);
offd2 = nu2 + s * (nu1 - tau * nu2);
offd2 = nu2 + s * (nu1 - tau * nu2);
// Apply rotation to V
jacobiRotateRight<j, k> (V, s, tau);
@@ -1038,7 +1038,7 @@ jacobiRotation (Matrix44<T>& A,
const T mu2 = T(2) * y;
// Let's see if rho^(-1) = mu2 / mu1 is less than tol
// This test also checks if rho^2 will overflow
// This test also checks if rho^2 will overflow
// when tol^(-1) < sqrt(limits<T>::max()).
if (std::abs(mu2) <= tol*std::abs(mu1))
{
@@ -1065,7 +1065,7 @@ jacobiRotation (Matrix44<T>& A,
const T nu1 = offd1;
const T nu2 = offd2;
offd1 -= s * (nu2 + tau * nu1);
offd2 += s * (nu1 - tau * nu2);
offd2 += s * (nu1 - tau * nu2);
}
{
@@ -1074,7 +1074,7 @@ jacobiRotation (Matrix44<T>& A,
const T nu1 = offd1;
const T nu2 = offd2;
offd1 -= s * (nu2 + tau * nu1);
offd2 += s * (nu1 - tau * nu2);
offd2 += s * (nu1 - tau * nu2);
}
jacobiRotateRight<j, k> (V, s, tau);
@@ -1119,8 +1119,8 @@ jacobiEigenSolver (Matrix33<T>& A,
{
// Z is for accumulating small changes (h) to diagonal entries
// of A for one sweep. Adding h's directly to A might cause
// a cancellation effect when h is relatively very small to
// the corresponding diagonal entry of A and
// a cancellation effect when h is relatively very small to
// the corresponding diagonal entry of A and
// this will increase numerical errors
Vec3<T> Z(0, 0, 0);
++numIter;