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// Copyright (c) 2014 libmv authors.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to
// deal in the Software without restriction, including without limitation the
// rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
// sell copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
#include "libmv/simple_pipeline/distortion_models.h"
#include "libmv/numeric/levenberg_marquardt.h"
namespace libmv {
namespace {
struct InvertPolynomialIntrinsicsCostFunction {
public:
typedef Vec2 FMatrixType;
typedef Vec2 XMatrixType;
InvertPolynomialIntrinsicsCostFunction(const double focal_length_x,
const double focal_length_y,
const double principal_point_x,
const double principal_point_y,
const double k1,
const double k2,
const double k3,
const double p1,
const double p2,
const double image_x,
const double image_y)
: focal_length_x_(focal_length_x),
focal_length_y_(focal_length_y),
principal_point_x_(principal_point_x),
principal_point_y_(principal_point_y),
k1_(k1), k2_(k2), k3_(k3),
p1_(p1), p2_(p2),
x_(image_x), y_(image_y) {}
Vec2 operator()(const Vec2 &u) const {
double xx, yy;
ApplyPolynomialDistortionModel(focal_length_x_,
focal_length_y_,
principal_point_x_,
principal_point_y_,
k1_, k2_, k3_,
p1_, p2_,
u(0), u(1),
&xx, &yy);
Vec2 fx;
fx << (xx - x_), (yy - y_);
return fx;
}
double focal_length_x_;
double focal_length_y_;
double principal_point_x_;
double principal_point_y_;
double k1_, k2_, k3_;
double p1_, p2_;
double x_, y_;
};
struct InvertDivisionIntrinsicsCostFunction {
public:
typedef Vec2 FMatrixType;
typedef Vec2 XMatrixType;
InvertDivisionIntrinsicsCostFunction(const double focal_length_x,
const double focal_length_y,
const double principal_point_x,
const double principal_point_y,
const double k1,
const double k2,
const double image_x,
const double image_y)
: focal_length_x_(focal_length_x),
focal_length_y_(focal_length_y),
principal_point_x_(principal_point_x),
principal_point_y_(principal_point_y),
k1_(k1), k2_(k2),
x_(image_x), y_(image_y) {}
Vec2 operator()(const Vec2 &u) const {
double xx, yy;
ApplyDivisionDistortionModel(focal_length_x_,
focal_length_y_,
principal_point_x_,
principal_point_y_,
k1_, k2_,
u(0), u(1),
&xx, &yy);
Vec2 fx;
fx << (xx - x_), (yy - y_);
return fx;
}
double focal_length_x_;
double focal_length_y_;
double principal_point_x_;
double principal_point_y_;
double k1_, k2_;
double x_, y_;
};
} // namespace
void InvertPolynomialDistortionModel(const double focal_length_x,
const double focal_length_y,
const double principal_point_x,
const double principal_point_y,
const double k1,
const double k2,
const double k3,
const double p1,
const double p2,
const double image_x,
const double image_y,
double *normalized_x,
double *normalized_y) {
// Compute the initial guess. For a camera with no distortion, this will also
// be the final answer; the LM iteration will terminate immediately.
Vec2 normalized;
normalized(0) = (image_x - principal_point_x) / focal_length_x;
normalized(1) = (image_y - principal_point_y) / focal_length_y;
typedef LevenbergMarquardt<InvertPolynomialIntrinsicsCostFunction> Solver;
InvertPolynomialIntrinsicsCostFunction intrinsics_cost(focal_length_x,
focal_length_y,
principal_point_x,
principal_point_y,
k1, k2, k3,
p1, p2,
image_x, image_y);
Solver::SolverParameters params;
Solver solver(intrinsics_cost);
/*Solver::Results results =*/ solver.minimize(params, &normalized);
// TODO(keir): Better error handling.
*normalized_x = normalized(0);
*normalized_y = normalized(1);
}
void InvertDivisionDistortionModel(const double focal_length_x,
const double focal_length_y,
const double principal_point_x,
const double principal_point_y,
const double k1,
const double k2,
const double image_x,
const double image_y,
double *normalized_x,
double *normalized_y) {
// Compute the initial guess. For a camera with no distortion, this will also
// be the final answer; the LM iteration will terminate immediately.
Vec2 normalized;
normalized(0) = (image_x - principal_point_x) / focal_length_x;
normalized(1) = (image_y - principal_point_y) / focal_length_y;
// TODO(sergey): Use Ceres minimizer instead.
typedef LevenbergMarquardt<InvertDivisionIntrinsicsCostFunction> Solver;
InvertDivisionIntrinsicsCostFunction intrinsics_cost(focal_length_x,
focal_length_y,
principal_point_x,
principal_point_y,
k1, k2,
image_x, image_y);
Solver::SolverParameters params;
Solver solver(intrinsics_cost);
/*Solver::Results results =*/ solver.minimize(params, &normalized);
// TODO(keir): Better error handling.
*normalized_x = normalized(0);
*normalized_y = normalized(1);
}
} // namespace libmv
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