630 lines
22 KiB
C++
630 lines
22 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
|
|
// Copyright 2015 Google Inc. All rights reserved.
|
|
// http://ceres-solver.org/
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without
|
|
// modification, are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistributions of source code must retain the above copyright notice,
|
|
// this list of conditions and the following disclaimer.
|
|
// * Redistributions in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
// * Neither the name of Google Inc. nor the names of its contributors may be
|
|
// used to endorse or promote products derived 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 A PARTICULAR PURPOSE
|
|
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
|
|
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
|
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
|
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
|
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
|
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
|
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
|
// POSSIBILITY OF SUCH DAMAGE.
|
|
//
|
|
// Author: keir@google.com (Keir Mierle)
|
|
// sameeragarwal@google.com (Sameer Agarwal)
|
|
//
|
|
// Templated functions for manipulating rotations. The templated
|
|
// functions are useful when implementing functors for automatic
|
|
// differentiation.
|
|
//
|
|
// In the following, the Quaternions are laid out as 4-vectors, thus:
|
|
//
|
|
// q[0] scalar part.
|
|
// q[1] coefficient of i.
|
|
// q[2] coefficient of j.
|
|
// q[3] coefficient of k.
|
|
//
|
|
// where: i*i = j*j = k*k = -1 and i*j = k, j*k = i, k*i = j.
|
|
|
|
#ifndef CERES_PUBLIC_ROTATION_H_
|
|
#define CERES_PUBLIC_ROTATION_H_
|
|
|
|
#include <algorithm>
|
|
#include <cmath>
|
|
#include <limits>
|
|
#include "glog/logging.h"
|
|
|
|
namespace ceres {
|
|
|
|
// Trivial wrapper to index linear arrays as matrices, given a fixed
|
|
// column and row stride. When an array "T* array" is wrapped by a
|
|
//
|
|
// (const) MatrixAdapter<T, row_stride, col_stride> M"
|
|
//
|
|
// the expression M(i, j) is equivalent to
|
|
//
|
|
// arrary[i * row_stride + j * col_stride]
|
|
//
|
|
// Conversion functions to and from rotation matrices accept
|
|
// MatrixAdapters to permit using row-major and column-major layouts,
|
|
// and rotation matrices embedded in larger matrices (such as a 3x4
|
|
// projection matrix).
|
|
template <typename T, int row_stride, int col_stride>
|
|
struct MatrixAdapter;
|
|
|
|
// Convenience functions to create a MatrixAdapter that treats the
|
|
// array pointed to by "pointer" as a 3x3 (contiguous) column-major or
|
|
// row-major matrix.
|
|
template <typename T>
|
|
MatrixAdapter<T, 1, 3> ColumnMajorAdapter3x3(T* pointer);
|
|
|
|
template <typename T>
|
|
MatrixAdapter<T, 3, 1> RowMajorAdapter3x3(T* pointer);
|
|
|
|
// Convert a value in combined axis-angle representation to a quaternion.
|
|
// The value angle_axis is a triple whose norm is an angle in radians,
|
|
// and whose direction is aligned with the axis of rotation,
|
|
// and quaternion is a 4-tuple that will contain the resulting quaternion.
|
|
// The implementation may be used with auto-differentiation up to the first
|
|
// derivative, higher derivatives may have unexpected results near the origin.
|
|
template<typename T>
|
|
void AngleAxisToQuaternion(const T* angle_axis, T* quaternion);
|
|
|
|
// Convert a quaternion to the equivalent combined axis-angle representation.
|
|
// The value quaternion must be a unit quaternion - it is not normalized first,
|
|
// and angle_axis will be filled with a value whose norm is the angle of
|
|
// rotation in radians, and whose direction is the axis of rotation.
|
|
// The implemention may be used with auto-differentiation up to the first
|
|
// derivative, higher derivatives may have unexpected results near the origin.
|
|
template<typename T>
|
|
void QuaternionToAngleAxis(const T* quaternion, T* angle_axis);
|
|
|
|
// Conversions between 3x3 rotation matrix (in column major order) and
|
|
// quaternion rotation representations. Templated for use with
|
|
// autodifferentiation.
|
|
template <typename T>
|
|
void RotationMatrixToQuaternion(const T* R, T* quaternion);
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void RotationMatrixToQuaternion(
|
|
const MatrixAdapter<const T, row_stride, col_stride>& R,
|
|
T* quaternion);
|
|
|
|
// Conversions between 3x3 rotation matrix (in column major order) and
|
|
// axis-angle rotation representations. Templated for use with
|
|
// autodifferentiation.
|
|
template <typename T>
|
|
void RotationMatrixToAngleAxis(const T* R, T* angle_axis);
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void RotationMatrixToAngleAxis(
|
|
const MatrixAdapter<const T, row_stride, col_stride>& R,
|
|
T* angle_axis);
|
|
|
|
template <typename T>
|
|
void AngleAxisToRotationMatrix(const T* angle_axis, T* R);
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void AngleAxisToRotationMatrix(
|
|
const T* angle_axis,
|
|
const MatrixAdapter<T, row_stride, col_stride>& R);
|
|
|
|
// Conversions between 3x3 rotation matrix (in row major order) and
|
|
// Euler angle (in degrees) rotation representations.
|
|
//
|
|
// The {pitch,roll,yaw} Euler angles are rotations around the {x,y,z}
|
|
// axes, respectively. They are applied in that same order, so the
|
|
// total rotation R is Rz * Ry * Rx.
|
|
template <typename T>
|
|
void EulerAnglesToRotationMatrix(const T* euler, int row_stride, T* R);
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void EulerAnglesToRotationMatrix(
|
|
const T* euler,
|
|
const MatrixAdapter<T, row_stride, col_stride>& R);
|
|
|
|
// Convert a 4-vector to a 3x3 scaled rotation matrix.
|
|
//
|
|
// The choice of rotation is such that the quaternion [1 0 0 0] goes to an
|
|
// identity matrix and for small a, b, c the quaternion [1 a b c] goes to
|
|
// the matrix
|
|
//
|
|
// [ 0 -c b ]
|
|
// I + 2 [ c 0 -a ] + higher order terms
|
|
// [ -b a 0 ]
|
|
//
|
|
// which corresponds to a Rodrigues approximation, the last matrix being
|
|
// the cross-product matrix of [a b c]. Together with the property that
|
|
// R(q1 * q2) = R(q1) * R(q2) this uniquely defines the mapping from q to R.
|
|
//
|
|
// No normalization of the quaternion is performed, i.e.
|
|
// R = ||q||^2 * Q, where Q is an orthonormal matrix
|
|
// such that det(Q) = 1 and Q*Q' = I
|
|
//
|
|
// WARNING: The rotation matrix is ROW MAJOR
|
|
template <typename T> inline
|
|
void QuaternionToScaledRotation(const T q[4], T R[3 * 3]);
|
|
|
|
template <typename T, int row_stride, int col_stride> inline
|
|
void QuaternionToScaledRotation(
|
|
const T q[4],
|
|
const MatrixAdapter<T, row_stride, col_stride>& R);
|
|
|
|
// Same as above except that the rotation matrix is normalized by the
|
|
// Frobenius norm, so that R * R' = I (and det(R) = 1).
|
|
//
|
|
// WARNING: The rotation matrix is ROW MAJOR
|
|
template <typename T> inline
|
|
void QuaternionToRotation(const T q[4], T R[3 * 3]);
|
|
|
|
template <typename T, int row_stride, int col_stride> inline
|
|
void QuaternionToRotation(
|
|
const T q[4],
|
|
const MatrixAdapter<T, row_stride, col_stride>& R);
|
|
|
|
// Rotates a point pt by a quaternion q:
|
|
//
|
|
// result = R(q) * pt
|
|
//
|
|
// Assumes the quaternion is unit norm. This assumption allows us to
|
|
// write the transform as (something)*pt + pt, as is clear from the
|
|
// formula below. If you pass in a quaternion with |q|^2 = 2 then you
|
|
// WILL NOT get back 2 times the result you get for a unit quaternion.
|
|
template <typename T> inline
|
|
void UnitQuaternionRotatePoint(const T q[4], const T pt[3], T result[3]);
|
|
|
|
// With this function you do not need to assume that q has unit norm.
|
|
// It does assume that the norm is non-zero.
|
|
template <typename T> inline
|
|
void QuaternionRotatePoint(const T q[4], const T pt[3], T result[3]);
|
|
|
|
// zw = z * w, where * is the Quaternion product between 4 vectors.
|
|
template<typename T> inline
|
|
void QuaternionProduct(const T z[4], const T w[4], T zw[4]);
|
|
|
|
// xy = x cross y;
|
|
template<typename T> inline
|
|
void CrossProduct(const T x[3], const T y[3], T x_cross_y[3]);
|
|
|
|
template<typename T> inline
|
|
T DotProduct(const T x[3], const T y[3]);
|
|
|
|
// y = R(angle_axis) * x;
|
|
template<typename T> inline
|
|
void AngleAxisRotatePoint(const T angle_axis[3], const T pt[3], T result[3]);
|
|
|
|
// --- IMPLEMENTATION
|
|
|
|
template<typename T, int row_stride, int col_stride>
|
|
struct MatrixAdapter {
|
|
T* pointer_;
|
|
explicit MatrixAdapter(T* pointer)
|
|
: pointer_(pointer)
|
|
{}
|
|
|
|
T& operator()(int r, int c) const {
|
|
return pointer_[r * row_stride + c * col_stride];
|
|
}
|
|
};
|
|
|
|
template <typename T>
|
|
MatrixAdapter<T, 1, 3> ColumnMajorAdapter3x3(T* pointer) {
|
|
return MatrixAdapter<T, 1, 3>(pointer);
|
|
}
|
|
|
|
template <typename T>
|
|
MatrixAdapter<T, 3, 1> RowMajorAdapter3x3(T* pointer) {
|
|
return MatrixAdapter<T, 3, 1>(pointer);
|
|
}
|
|
|
|
template<typename T>
|
|
inline void AngleAxisToQuaternion(const T* angle_axis, T* quaternion) {
|
|
const T& a0 = angle_axis[0];
|
|
const T& a1 = angle_axis[1];
|
|
const T& a2 = angle_axis[2];
|
|
const T theta_squared = a0 * a0 + a1 * a1 + a2 * a2;
|
|
|
|
// For points not at the origin, the full conversion is numerically stable.
|
|
if (theta_squared > T(0.0)) {
|
|
const T theta = sqrt(theta_squared);
|
|
const T half_theta = theta * T(0.5);
|
|
const T k = sin(half_theta) / theta;
|
|
quaternion[0] = cos(half_theta);
|
|
quaternion[1] = a0 * k;
|
|
quaternion[2] = a1 * k;
|
|
quaternion[3] = a2 * k;
|
|
} else {
|
|
// At the origin, sqrt() will produce NaN in the derivative since
|
|
// the argument is zero. By approximating with a Taylor series,
|
|
// and truncating at one term, the value and first derivatives will be
|
|
// computed correctly when Jets are used.
|
|
const T k(0.5);
|
|
quaternion[0] = T(1.0);
|
|
quaternion[1] = a0 * k;
|
|
quaternion[2] = a1 * k;
|
|
quaternion[3] = a2 * k;
|
|
}
|
|
}
|
|
|
|
template<typename T>
|
|
inline void QuaternionToAngleAxis(const T* quaternion, T* angle_axis) {
|
|
const T& q1 = quaternion[1];
|
|
const T& q2 = quaternion[2];
|
|
const T& q3 = quaternion[3];
|
|
const T sin_squared_theta = q1 * q1 + q2 * q2 + q3 * q3;
|
|
|
|
// For quaternions representing non-zero rotation, the conversion
|
|
// is numerically stable.
|
|
if (sin_squared_theta > T(0.0)) {
|
|
const T sin_theta = sqrt(sin_squared_theta);
|
|
const T& cos_theta = quaternion[0];
|
|
|
|
// If cos_theta is negative, theta is greater than pi/2, which
|
|
// means that angle for the angle_axis vector which is 2 * theta
|
|
// would be greater than pi.
|
|
//
|
|
// While this will result in the correct rotation, it does not
|
|
// result in a normalized angle-axis vector.
|
|
//
|
|
// In that case we observe that 2 * theta ~ 2 * theta - 2 * pi,
|
|
// which is equivalent saying
|
|
//
|
|
// theta - pi = atan(sin(theta - pi), cos(theta - pi))
|
|
// = atan(-sin(theta), -cos(theta))
|
|
//
|
|
const T two_theta =
|
|
T(2.0) * ((cos_theta < 0.0)
|
|
? atan2(-sin_theta, -cos_theta)
|
|
: atan2(sin_theta, cos_theta));
|
|
const T k = two_theta / sin_theta;
|
|
angle_axis[0] = q1 * k;
|
|
angle_axis[1] = q2 * k;
|
|
angle_axis[2] = q3 * k;
|
|
} else {
|
|
// For zero rotation, sqrt() will produce NaN in the derivative since
|
|
// the argument is zero. By approximating with a Taylor series,
|
|
// and truncating at one term, the value and first derivatives will be
|
|
// computed correctly when Jets are used.
|
|
const T k(2.0);
|
|
angle_axis[0] = q1 * k;
|
|
angle_axis[1] = q2 * k;
|
|
angle_axis[2] = q3 * k;
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
void RotationMatrixToQuaternion(const T* R, T* angle_axis) {
|
|
RotationMatrixToQuaternion(ColumnMajorAdapter3x3(R), angle_axis);
|
|
}
|
|
|
|
// This algorithm comes from "Quaternion Calculus and Fast Animation",
|
|
// Ken Shoemake, 1987 SIGGRAPH course notes
|
|
template <typename T, int row_stride, int col_stride>
|
|
void RotationMatrixToQuaternion(
|
|
const MatrixAdapter<const T, row_stride, col_stride>& R,
|
|
T* quaternion) {
|
|
const T trace = R(0, 0) + R(1, 1) + R(2, 2);
|
|
if (trace >= 0.0) {
|
|
T t = sqrt(trace + T(1.0));
|
|
quaternion[0] = T(0.5) * t;
|
|
t = T(0.5) / t;
|
|
quaternion[1] = (R(2, 1) - R(1, 2)) * t;
|
|
quaternion[2] = (R(0, 2) - R(2, 0)) * t;
|
|
quaternion[3] = (R(1, 0) - R(0, 1)) * t;
|
|
} else {
|
|
int i = 0;
|
|
if (R(1, 1) > R(0, 0)) {
|
|
i = 1;
|
|
}
|
|
|
|
if (R(2, 2) > R(i, i)) {
|
|
i = 2;
|
|
}
|
|
|
|
const int j = (i + 1) % 3;
|
|
const int k = (j + 1) % 3;
|
|
T t = sqrt(R(i, i) - R(j, j) - R(k, k) + T(1.0));
|
|
quaternion[i + 1] = T(0.5) * t;
|
|
t = T(0.5) / t;
|
|
quaternion[0] = (R(k, j) - R(j, k)) * t;
|
|
quaternion[j + 1] = (R(j, i) + R(i, j)) * t;
|
|
quaternion[k + 1] = (R(k, i) + R(i, k)) * t;
|
|
}
|
|
}
|
|
|
|
// The conversion of a rotation matrix to the angle-axis form is
|
|
// numerically problematic when then rotation angle is close to zero
|
|
// or to Pi. The following implementation detects when these two cases
|
|
// occurs and deals with them by taking code paths that are guaranteed
|
|
// to not perform division by a small number.
|
|
template <typename T>
|
|
inline void RotationMatrixToAngleAxis(const T* R, T* angle_axis) {
|
|
RotationMatrixToAngleAxis(ColumnMajorAdapter3x3(R), angle_axis);
|
|
}
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void RotationMatrixToAngleAxis(
|
|
const MatrixAdapter<const T, row_stride, col_stride>& R,
|
|
T* angle_axis) {
|
|
T quaternion[4];
|
|
RotationMatrixToQuaternion(R, quaternion);
|
|
QuaternionToAngleAxis(quaternion, angle_axis);
|
|
return;
|
|
}
|
|
|
|
template <typename T>
|
|
inline void AngleAxisToRotationMatrix(const T* angle_axis, T* R) {
|
|
AngleAxisToRotationMatrix(angle_axis, ColumnMajorAdapter3x3(R));
|
|
}
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void AngleAxisToRotationMatrix(
|
|
const T* angle_axis,
|
|
const MatrixAdapter<T, row_stride, col_stride>& R) {
|
|
static const T kOne = T(1.0);
|
|
const T theta2 = DotProduct(angle_axis, angle_axis);
|
|
if (theta2 > T(std::numeric_limits<double>::epsilon())) {
|
|
// We want to be careful to only evaluate the square root if the
|
|
// norm of the angle_axis vector is greater than zero. Otherwise
|
|
// we get a division by zero.
|
|
const T theta = sqrt(theta2);
|
|
const T wx = angle_axis[0] / theta;
|
|
const T wy = angle_axis[1] / theta;
|
|
const T wz = angle_axis[2] / theta;
|
|
|
|
const T costheta = cos(theta);
|
|
const T sintheta = sin(theta);
|
|
|
|
R(0, 0) = costheta + wx*wx*(kOne - costheta);
|
|
R(1, 0) = wz*sintheta + wx*wy*(kOne - costheta);
|
|
R(2, 0) = -wy*sintheta + wx*wz*(kOne - costheta);
|
|
R(0, 1) = wx*wy*(kOne - costheta) - wz*sintheta;
|
|
R(1, 1) = costheta + wy*wy*(kOne - costheta);
|
|
R(2, 1) = wx*sintheta + wy*wz*(kOne - costheta);
|
|
R(0, 2) = wy*sintheta + wx*wz*(kOne - costheta);
|
|
R(1, 2) = -wx*sintheta + wy*wz*(kOne - costheta);
|
|
R(2, 2) = costheta + wz*wz*(kOne - costheta);
|
|
} else {
|
|
// Near zero, we switch to using the first order Taylor expansion.
|
|
R(0, 0) = kOne;
|
|
R(1, 0) = angle_axis[2];
|
|
R(2, 0) = -angle_axis[1];
|
|
R(0, 1) = -angle_axis[2];
|
|
R(1, 1) = kOne;
|
|
R(2, 1) = angle_axis[0];
|
|
R(0, 2) = angle_axis[1];
|
|
R(1, 2) = -angle_axis[0];
|
|
R(2, 2) = kOne;
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
inline void EulerAnglesToRotationMatrix(const T* euler,
|
|
const int row_stride_parameter,
|
|
T* R) {
|
|
CHECK_EQ(row_stride_parameter, 3);
|
|
EulerAnglesToRotationMatrix(euler, RowMajorAdapter3x3(R));
|
|
}
|
|
|
|
template <typename T, int row_stride, int col_stride>
|
|
void EulerAnglesToRotationMatrix(
|
|
const T* euler,
|
|
const MatrixAdapter<T, row_stride, col_stride>& R) {
|
|
const double kPi = 3.14159265358979323846;
|
|
const T degrees_to_radians(kPi / 180.0);
|
|
|
|
const T pitch(euler[0] * degrees_to_radians);
|
|
const T roll(euler[1] * degrees_to_radians);
|
|
const T yaw(euler[2] * degrees_to_radians);
|
|
|
|
const T c1 = cos(yaw);
|
|
const T s1 = sin(yaw);
|
|
const T c2 = cos(roll);
|
|
const T s2 = sin(roll);
|
|
const T c3 = cos(pitch);
|
|
const T s3 = sin(pitch);
|
|
|
|
R(0, 0) = c1*c2;
|
|
R(0, 1) = -s1*c3 + c1*s2*s3;
|
|
R(0, 2) = s1*s3 + c1*s2*c3;
|
|
|
|
R(1, 0) = s1*c2;
|
|
R(1, 1) = c1*c3 + s1*s2*s3;
|
|
R(1, 2) = -c1*s3 + s1*s2*c3;
|
|
|
|
R(2, 0) = -s2;
|
|
R(2, 1) = c2*s3;
|
|
R(2, 2) = c2*c3;
|
|
}
|
|
|
|
template <typename T> inline
|
|
void QuaternionToScaledRotation(const T q[4], T R[3 * 3]) {
|
|
QuaternionToScaledRotation(q, RowMajorAdapter3x3(R));
|
|
}
|
|
|
|
template <typename T, int row_stride, int col_stride> inline
|
|
void QuaternionToScaledRotation(
|
|
const T q[4],
|
|
const MatrixAdapter<T, row_stride, col_stride>& R) {
|
|
// Make convenient names for elements of q.
|
|
T a = q[0];
|
|
T b = q[1];
|
|
T c = q[2];
|
|
T d = q[3];
|
|
// This is not to eliminate common sub-expression, but to
|
|
// make the lines shorter so that they fit in 80 columns!
|
|
T aa = a * a;
|
|
T ab = a * b;
|
|
T ac = a * c;
|
|
T ad = a * d;
|
|
T bb = b * b;
|
|
T bc = b * c;
|
|
T bd = b * d;
|
|
T cc = c * c;
|
|
T cd = c * d;
|
|
T dd = d * d;
|
|
|
|
R(0, 0) = aa + bb - cc - dd; R(0, 1) = T(2) * (bc - ad); R(0, 2) = T(2) * (ac + bd); // NOLINT
|
|
R(1, 0) = T(2) * (ad + bc); R(1, 1) = aa - bb + cc - dd; R(1, 2) = T(2) * (cd - ab); // NOLINT
|
|
R(2, 0) = T(2) * (bd - ac); R(2, 1) = T(2) * (ab + cd); R(2, 2) = aa - bb - cc + dd; // NOLINT
|
|
}
|
|
|
|
template <typename T> inline
|
|
void QuaternionToRotation(const T q[4], T R[3 * 3]) {
|
|
QuaternionToRotation(q, RowMajorAdapter3x3(R));
|
|
}
|
|
|
|
template <typename T, int row_stride, int col_stride> inline
|
|
void QuaternionToRotation(const T q[4],
|
|
const MatrixAdapter<T, row_stride, col_stride>& R) {
|
|
QuaternionToScaledRotation(q, R);
|
|
|
|
T normalizer = q[0]*q[0] + q[1]*q[1] + q[2]*q[2] + q[3]*q[3];
|
|
CHECK_NE(normalizer, T(0));
|
|
normalizer = T(1) / normalizer;
|
|
|
|
for (int i = 0; i < 3; ++i) {
|
|
for (int j = 0; j < 3; ++j) {
|
|
R(i, j) *= normalizer;
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename T> inline
|
|
void UnitQuaternionRotatePoint(const T q[4], const T pt[3], T result[3]) {
|
|
const T t2 = q[0] * q[1];
|
|
const T t3 = q[0] * q[2];
|
|
const T t4 = q[0] * q[3];
|
|
const T t5 = -q[1] * q[1];
|
|
const T t6 = q[1] * q[2];
|
|
const T t7 = q[1] * q[3];
|
|
const T t8 = -q[2] * q[2];
|
|
const T t9 = q[2] * q[3];
|
|
const T t1 = -q[3] * q[3];
|
|
result[0] = T(2) * ((t8 + t1) * pt[0] + (t6 - t4) * pt[1] + (t3 + t7) * pt[2]) + pt[0]; // NOLINT
|
|
result[1] = T(2) * ((t4 + t6) * pt[0] + (t5 + t1) * pt[1] + (t9 - t2) * pt[2]) + pt[1]; // NOLINT
|
|
result[2] = T(2) * ((t7 - t3) * pt[0] + (t2 + t9) * pt[1] + (t5 + t8) * pt[2]) + pt[2]; // NOLINT
|
|
}
|
|
|
|
template <typename T> inline
|
|
void QuaternionRotatePoint(const T q[4], const T pt[3], T result[3]) {
|
|
// 'scale' is 1 / norm(q).
|
|
const T scale = T(1) / sqrt(q[0] * q[0] +
|
|
q[1] * q[1] +
|
|
q[2] * q[2] +
|
|
q[3] * q[3]);
|
|
|
|
// Make unit-norm version of q.
|
|
const T unit[4] = {
|
|
scale * q[0],
|
|
scale * q[1],
|
|
scale * q[2],
|
|
scale * q[3],
|
|
};
|
|
|
|
UnitQuaternionRotatePoint(unit, pt, result);
|
|
}
|
|
|
|
template<typename T> inline
|
|
void QuaternionProduct(const T z[4], const T w[4], T zw[4]) {
|
|
zw[0] = z[0] * w[0] - z[1] * w[1] - z[2] * w[2] - z[3] * w[3];
|
|
zw[1] = z[0] * w[1] + z[1] * w[0] + z[2] * w[3] - z[3] * w[2];
|
|
zw[2] = z[0] * w[2] - z[1] * w[3] + z[2] * w[0] + z[3] * w[1];
|
|
zw[3] = z[0] * w[3] + z[1] * w[2] - z[2] * w[1] + z[3] * w[0];
|
|
}
|
|
|
|
// xy = x cross y;
|
|
template<typename T> inline
|
|
void CrossProduct(const T x[3], const T y[3], T x_cross_y[3]) {
|
|
x_cross_y[0] = x[1] * y[2] - x[2] * y[1];
|
|
x_cross_y[1] = x[2] * y[0] - x[0] * y[2];
|
|
x_cross_y[2] = x[0] * y[1] - x[1] * y[0];
|
|
}
|
|
|
|
template<typename T> inline
|
|
T DotProduct(const T x[3], const T y[3]) {
|
|
return (x[0] * y[0] + x[1] * y[1] + x[2] * y[2]);
|
|
}
|
|
|
|
template<typename T> inline
|
|
void AngleAxisRotatePoint(const T angle_axis[3], const T pt[3], T result[3]) {
|
|
const T theta2 = DotProduct(angle_axis, angle_axis);
|
|
if (theta2 > T(std::numeric_limits<double>::epsilon())) {
|
|
// Away from zero, use the rodriguez formula
|
|
//
|
|
// result = pt costheta +
|
|
// (w x pt) * sintheta +
|
|
// w (w . pt) (1 - costheta)
|
|
//
|
|
// We want to be careful to only evaluate the square root if the
|
|
// norm of the angle_axis vector is greater than zero. Otherwise
|
|
// we get a division by zero.
|
|
//
|
|
const T theta = sqrt(theta2);
|
|
const T costheta = cos(theta);
|
|
const T sintheta = sin(theta);
|
|
const T theta_inverse = 1.0 / theta;
|
|
|
|
const T w[3] = { angle_axis[0] * theta_inverse,
|
|
angle_axis[1] * theta_inverse,
|
|
angle_axis[2] * theta_inverse };
|
|
|
|
// Explicitly inlined evaluation of the cross product for
|
|
// performance reasons.
|
|
const T w_cross_pt[3] = { w[1] * pt[2] - w[2] * pt[1],
|
|
w[2] * pt[0] - w[0] * pt[2],
|
|
w[0] * pt[1] - w[1] * pt[0] };
|
|
const T tmp =
|
|
(w[0] * pt[0] + w[1] * pt[1] + w[2] * pt[2]) * (T(1.0) - costheta);
|
|
|
|
result[0] = pt[0] * costheta + w_cross_pt[0] * sintheta + w[0] * tmp;
|
|
result[1] = pt[1] * costheta + w_cross_pt[1] * sintheta + w[1] * tmp;
|
|
result[2] = pt[2] * costheta + w_cross_pt[2] * sintheta + w[2] * tmp;
|
|
} else {
|
|
// Near zero, the first order Taylor approximation of the rotation
|
|
// matrix R corresponding to a vector w and angle w is
|
|
//
|
|
// R = I + hat(w) * sin(theta)
|
|
//
|
|
// But sintheta ~ theta and theta * w = angle_axis, which gives us
|
|
//
|
|
// R = I + hat(w)
|
|
//
|
|
// and actually performing multiplication with the point pt, gives us
|
|
// R * pt = pt + w x pt.
|
|
//
|
|
// Switching to the Taylor expansion near zero provides meaningful
|
|
// derivatives when evaluated using Jets.
|
|
//
|
|
// Explicitly inlined evaluation of the cross product for
|
|
// performance reasons.
|
|
const T w_cross_pt[3] = { angle_axis[1] * pt[2] - angle_axis[2] * pt[1],
|
|
angle_axis[2] * pt[0] - angle_axis[0] * pt[2],
|
|
angle_axis[0] * pt[1] - angle_axis[1] * pt[0] };
|
|
|
|
result[0] = pt[0] + w_cross_pt[0];
|
|
result[1] = pt[1] + w_cross_pt[1];
|
|
result[2] = pt[2] + w_cross_pt[2];
|
|
}
|
|
}
|
|
|
|
} // namespace ceres
|
|
|
|
#endif // CERES_PUBLIC_ROTATION_H_
|