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/*M///////////////////////////////////////////////////////////////////////////////////////
|
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//
|
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
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//
|
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// By downloading, copying, installing or using the software you agree to this license.
|
||||
// If you do not agree to this license, do not download, install,
|
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// copy or use the software.
|
||||
//
|
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//
|
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// License Agreement
|
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// For Open Source Computer Vision Library
|
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//
|
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
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// Copyright (C) 2008-2013, Willow Garage Inc., all rights reserved.
|
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// Third party copyrights are property of their respective owners.
|
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//
|
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// Redistribution and use in source and binary forms, with or without modification,
|
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// are permitted provided that the following conditions are met:
|
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//
|
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// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
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//
|
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// * Redistribution's in binary form must reproduce the above copyright notice,
|
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// this list of conditions and the following disclaimer in the documentation
|
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// and / or other materials provided with the distribution.
|
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//
|
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// * The name of the copyright holders may not be used to endorse or promote products
|
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// derived from this software without specific prior written permission.
|
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//
|
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// This software is provided by the copyright holders and contributors "as is" and
|
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// any express or implied warranties, including, but not limited to, the implied
|
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
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// In no event shall the Intel Corporation or contributors be liable for any direct,
|
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// indirect, incidental, special, exemplary, or consequential damages
|
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// (including, but not limited to, procurement of substitute goods or services;
|
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// loss of use, data, or profits; or business interruption) however caused
|
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// and on any theory of liability, whether in contract, strict liability,
|
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// or tort (including negligence or otherwise) arising in any way out of
|
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp" |
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#include "opencv2/core/affine.hpp" |
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#include "opencv2/calib3d.hpp" |
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#include <iostream> |
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TEST(Calib3d_Affine3f, accuracy) |
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{ |
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cv::Vec3d rvec(0.2, 0.5, 0.3); |
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cv::Affine3d affine(rvec); |
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cv::Mat expected; |
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cv::Rodrigues(rvec, expected); |
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ASSERT_EQ(0, norm(cv::Mat(affine.matrix, false).colRange(0, 3).rowRange(0, 3) != expected)); |
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ASSERT_EQ(0, norm(cv::Mat(affine.linear()) != expected)); |
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cv::Matx33d R = cv::Matx33d::eye(); |
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double angle = 50; |
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R.val[0] = R.val[4] = std::cos(CV_PI*angle/180.0); |
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R.val[3] = std::sin(CV_PI*angle/180.0); |
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R.val[1] = -R.val[3]; |
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cv::Affine3d affine1(cv::Mat(cv::Vec3d(0.2, 0.5, 0.3)).reshape(1, 1), cv::Vec3d(4, 5, 6)); |
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cv::Affine3d affine2(R, cv::Vec3d(1, 1, 0.4)); |
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cv::Affine3d result = affine1.inv() * affine2; |
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expected = cv::Mat(affine1.matrix.inv(cv::DECOMP_SVD)) * cv::Mat(affine2.matrix, false); |
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cv::Mat diff; |
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cv::absdiff(expected, result.matrix, diff); |
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ASSERT_LT(cv::norm(diff, cv::NORM_INF), 1e-15); |
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} |
@ -0,0 +1,386 @@ |
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/*M///////////////////////////////////////////////////////////////////////////////////////
|
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//
|
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
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//
|
||||
// By downloading, copying, installing or using the software you agree to this license.
|
||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
|
||||
//
|
||||
//
|
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// License Agreement
|
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// For Open Source Computer Vision Library
|
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//
|
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
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// Copyright (C) 2008-2013, Willow Garage Inc., all rights reserved.
|
||||
// Third party copyrights are property of their respective owners.
|
||||
//
|
||||
// Redistribution and use in source and binary forms, with or without modification,
|
||||
// are permitted provided that the following conditions are met:
|
||||
//
|
||||
// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
|
||||
// * Redistribution's 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.
|
||||
//
|
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// * The name of the copyright holders may not be used to endorse or promote products
|
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// derived from this software without specific prior written permission.
|
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//
|
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// This software is provided by the copyright holders and contributors "as is" and
|
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// any express or implied warranties, including, but not limited to, the implied
|
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
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// In no event shall the Intel Corporation or contributors be liable for any direct,
|
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// indirect, incidental, special, exemplary, or consequential damages
|
||||
// (including, but not limited to, procurement of substitute goods or services;
|
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// loss of use, data, or profits; or business interruption) however caused
|
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// and on any theory of liability, whether in contract, strict liability,
|
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_CORE_AFFINE3_HPP__ |
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#define __OPENCV_CORE_AFFINE3_HPP__ |
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#ifdef __cplusplus |
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#include <opencv2/core.hpp> |
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namespace cv |
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{ |
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template<typename T> |
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class CV_EXPORTS Affine3 |
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{ |
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public: |
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typedef T float_type; |
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typedef cv::Matx<float_type, 3, 3> Mat3; |
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typedef cv::Matx<float_type, 4, 4> Mat4; |
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typedef cv::Vec<float_type, 3> Vec3; |
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Affine3(); |
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//Augmented affine matrix
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Affine3(const Mat4& affine); |
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//Rotation matrix
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Affine3(const Mat3& R, const Vec3& t = Vec3::all(0)); |
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//Rodrigues vector
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Affine3(const Vec3& rvec, const Vec3& t = Vec3::all(0)); |
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//Combines all contructors above. Supports 4x4, 3x3, 1x3, 3x1 sizes of data matrix
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explicit Affine3(const cv::Mat& data, const Vec3& t = Vec3::all(0)); |
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//Euler angles
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Affine3(float_type alpha, float_type beta, float_type gamma, const Vec3& t = Vec3::all(0)); |
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static Affine3 Identity(); |
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//Rotation matrix
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void rotation(const Mat3& R); |
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//Rodrigues vector
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void rotation(const Vec3& rvec); |
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//Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix;
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void rotation(const Mat& data); |
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//Euler angles
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void rotation(float_type alpha, float_type beta, float_type gamma); |
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void linear(const Mat3& L); |
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void translation(const Vec3& t); |
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Mat3 rotation() const; |
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Mat3 linear() const; |
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Vec3 translation() const; |
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Affine3 inv(int method = cv::DECOMP_SVD) const; |
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// a.rotate(R) is equivalent to Affine(R, 0) * a;
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Affine3 rotate(const Mat3& R) const; |
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// a.translate(t) is equivalent to Affine(E, t) * a;
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Affine3 translate(const Vec3& t) const; |
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// a.concatenate(affine) is equivalent to affine * a;
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Affine3 concatenate(const Affine3& affine) const; |
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template <typename Y> operator Affine3<Y>() const; |
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Mat4 matrix; |
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#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H |
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Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine); |
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Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine); |
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operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const; |
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operator Eigen::Transform<T, 3, Eigen::Affine>() const; |
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#endif |
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}; |
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template<typename T> Affine3<T> operator*(const Affine3<T>& affine1, const Affine3<T>& affine2); |
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template<typename T, typename V> V operator*(const Affine3<T>& affine, const V& vector); |
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typedef Affine3<float> Affine3f; |
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typedef Affine3<double> Affine3d; |
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cv::Vec3f operator*(const cv::Affine3f& affine, const cv::Vec3f& vector); |
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cv::Vec3d operator*(const cv::Affine3d& affine, const cv::Vec3d& vector); |
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} |
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///////////////////////////////////////////////////////////////////////////////////
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/// Implementaiton
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template<typename T> inline cv::Affine3<T>::Affine3() : matrix(Mat4::eye()) {} |
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template<typename T> inline cv::Affine3<T>::Affine3(const Mat4& affine) : matrix(affine) {} |
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template<typename T> inline cv::Affine3<T>::Affine3(const Mat3& R, const Vec3& t) |
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{ |
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rotation(R); |
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translation(t); |
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matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; |
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matrix.val[15] = 1; |
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} |
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template<typename T> inline cv::Affine3<T>::Affine3(const Vec3& rvec, const Vec3& t) |
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{ |
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rotation(rvec); |
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translation(t); |
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matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; |
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matrix.val[15] = 1; |
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} |
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template<typename T> inline cv::Affine3<T>::Affine3(const cv::Mat& data, const Vec3& t) |
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{ |
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CV_Assert(data.type() == cv::DataType<T>::type); |
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if (data.cols == 4 && data.rows == 4) |
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{ |
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data.copyTo(matrix); |
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return; |
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} |
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rotation(data); |
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translation(t); |
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matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; |
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matrix.val[15] = 1; |
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} |
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template<typename T> inline cv::Affine3<T>::Affine3(float_type alpha, float_type beta, float_type gamma, const Vec3& t) |
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{ |
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rotation(alpha, beta, gamma); |
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translation(t); |
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matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; |
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matrix.val[15] = 1; |
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} |
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template<typename T> inline cv::Affine3<T> cv::Affine3<T>::Identity() |
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{ |
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return Affine3<T>(cv::Affine3<T>::Mat4::eye()); |
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} |
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template<typename T> inline void cv::Affine3<T>::rotation(const Mat3& R) { linear(R); } |
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template<typename T> inline void cv::Affine3<T>::rotation(const Vec3& rvec) |
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{ |
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double rx = rvec[0], ry = rvec[1], rz = rvec[2]; |
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double theta = std::sqrt(rx*rx + ry*ry + rz*rz); |
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if (theta < DBL_EPSILON) |
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rotation(Mat3::eye()); |
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else |
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{ |
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const double I[] = { 1, 0, 0, 0, 1, 0, 0, 0, 1 }; |
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double c = std::cos(theta); |
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double s = std::sin(theta); |
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double c1 = 1. - c; |
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double itheta = theta ? 1./theta : 0.; |
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rx *= itheta; ry *= itheta; rz *= itheta; |
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double rrt[] = { rx*rx, rx*ry, rx*rz, rx*ry, ry*ry, ry*rz, rx*rz, ry*rz, rz*rz }; |
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double _r_x_[] = { 0, -rz, ry, rz, 0, -rx, -ry, rx, 0 }; |
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Mat3 R; |
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// R = cos(theta)*I + (1 - cos(theta))*r*rT + sin(theta)*[r_x]
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// where [r_x] is [0 -rz ry; rz 0 -rx; -ry rx 0]
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for(int k = 0; k < 9; ++k) |
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R.val[k] = static_cast<float_type>(c*I[k] + c1*rrt[k] + s*_r_x_[k]); |
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rotation(R); |
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} |
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} |
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//Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix;
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template<typename T> inline void cv::Affine3<T>::rotation(const cv::Mat& data) |
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{ |
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CV_Assert(data.type() == cv::DataType<T>::type); |
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if (data.cols == 3 && data.rows == 3) |
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{ |
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Mat3 R; |
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data.copyTo(R); |
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rotation(R); |
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} |
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else if ((data.cols == 3 && data.rows == 1) || (data.cols == 1 && data.rows == 3)) |
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{ |
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Vec3 rvec; |
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data.reshape(1, 3).copyTo(rvec); |
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rotation(rvec); |
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} |
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else |
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CV_Assert(!"Input marix can be 3x3, 1x3 or 3x1"); |
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} |
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template<typename T> inline void cv::Affine3<T>::rotation(float_type alpha, float_type beta, float_type gamma) |
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{ |
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rotation(Vec3(alpha, beta, gamma)); |
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} |
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template<typename T> inline void cv::Affine3<T>::linear(const Mat3& L) |
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{ |
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matrix.val[0] = L.val[0]; matrix.val[1] = L.val[1]; matrix.val[ 2] = L.val[2]; |
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matrix.val[4] = L.val[3]; matrix.val[5] = L.val[4]; matrix.val[ 6] = L.val[5]; |
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matrix.val[8] = L.val[6]; matrix.val[9] = L.val[7]; matrix.val[10] = L.val[8]; |
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} |
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template<typename T> inline void cv::Affine3<T>::translation(const Vec3& t) |
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{ |
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matrix.val[3] = t[0]; matrix.val[7] = t[1]; matrix.val[11] = t[2]; |
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} |
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template<typename T> inline typename cv::Affine3<T>::Mat3 cv::Affine3<T>::rotation() const { return linear(); } |
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template<typename T> inline typename cv::Affine3<T>::Mat3 cv::Affine3<T>::linear() const |
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{ |
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cv::Affine3<T>::Mat3 R; |
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R.val[0] = matrix.val[0]; R.val[1] = matrix.val[1]; R.val[2] = matrix.val[ 2]; |
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R.val[3] = matrix.val[4]; R.val[4] = matrix.val[5]; R.val[5] = matrix.val[ 6]; |
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R.val[6] = matrix.val[8]; R.val[7] = matrix.val[9]; R.val[8] = matrix.val[10]; |
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return R; |
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} |
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template<typename T> inline typename cv::Affine3<T>::Vec3 cv::Affine3<T>::translation() const |
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{ |
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return Vec3(matrix.val[3], matrix.val[7], matrix.val[11]); |
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} |
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template<typename T> inline cv::Affine3<T> cv::Affine3<T>::inv(int method) const |
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{ |
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return matrix.inv(method); |
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} |
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template<typename T> inline cv::Affine3<T> cv::Affine3<T>::rotate(const Mat3& R) const |
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{ |
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Mat3 Lc = linear(); |
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Vec3 tc = translation(); |
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Mat4 result; |
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result.val[12] = result.val[13] = result.val[14] = 0; |
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result.val[15] = 1; |
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for(int j = 0; j < 3; ++j) |
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{ |
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for(int i = 0; i < 3; ++i) |
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{ |
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float_type value = 0; |
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for(int k = 0; k < 3; ++k) |
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value += R(j, k) * Lc(k, i); |
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result(j, i) = value; |
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} |
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result(j, 3) = R.row(j).dot(tc.t()); |
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} |
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return result; |
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} |
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template<typename T> inline cv::Affine3<T> cv::Affine3<T>::translate(const Vec3& t) const |
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{ |
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Mat4 m = matrix; |
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m.val[ 3] += t[0]; |
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m.val[ 7] += t[1]; |
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m.val[11] += t[2]; |
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return m; |
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} |
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template<typename T> inline cv::Affine3<T> cv::Affine3<T>::concatenate(const Affine3<T>& affine) const |
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{ |
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return (*this).rotate(affine.rotation()).translate(affine.translation()); |
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} |
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template<typename T> template <typename Y> inline cv::Affine3<T>::operator Affine3<Y>() const |
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{ |
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return Affine3<Y>(matrix); |
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} |
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template<typename T> inline cv::Affine3<T> cv::operator*(const cv::Affine3<T>& affine1, const cv::Affine3<T>& affine2) |
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{ |
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return affine2.concatenate(affine1); |
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} |
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template<typename T, typename V> inline V cv::operator*(const cv::Affine3<T>& affine, const V& v) |
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{ |
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const typename Affine3<T>::Mat4& m = affine.matrix; |
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V r; |
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r.x = m.val[0] * v.x + m.val[1] * v.y + m.val[ 2] * v.z + m.val[ 3]; |
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r.y = m.val[4] * v.x + m.val[5] * v.y + m.val[ 6] * v.z + m.val[ 7]; |
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r.z = m.val[8] * v.x + m.val[9] * v.y + m.val[10] * v.z + m.val[11]; |
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return r; |
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} |
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inline cv::Vec3f cv::operator*(const cv::Affine3f& affine, const cv::Vec3f& v) |
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{ |
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const cv::Matx44f& m = affine.matrix; |
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cv::Vec3f r; |
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r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3]; |
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r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7]; |
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r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11]; |
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return r; |
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} |
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inline cv::Vec3d cv::operator*(const cv::Affine3d& affine, const cv::Vec3d& v) |
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{ |
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const cv::Matx44d& m = affine.matrix; |
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cv::Vec3d r; |
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r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3]; |
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r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7]; |
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r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11]; |
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return r; |
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} |
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#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H |
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template<typename T> inline cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine) |
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{ |
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cv::Mat(4, 4, cv::DataType<T>::type, affine.matrix().data()).copyTo(matrix); |
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} |
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template<typename T> inline cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine) |
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{ |
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Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> a = affine; |
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cv::Mat(4, 4, cv::DataType<T>::type, a.matrix().data()).copyTo(matrix); |
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} |
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template<typename T> inline cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const |
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{ |
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Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> r; |
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cv::Mat hdr(4, 4, cv::DataType<T>::type, r.matrix().data()); |
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cv::Mat(matrix, false).copyTo(hdr); |
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return r; |
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} |
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|
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template<typename T> inline cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine>() const |
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{ |
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return this->operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>(); |
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} |
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#endif /* defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H */ |
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|
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#endif /* __cplusplus */ |
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#endif /* __OPENCV_CORE_AFFINE3_HPP__ */ |
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Reference in new issue