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Commit 6882c10b authored by Thomas Dunker's avatar Thomas Dunker
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Extension of the camera distortion model for tilted image sensors (Scheimpflug… 

Extension of the camera distortion model for tilted image sensors (Scheimpflug condition) including test
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doc/opencv.bib
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......@@ -415,6 +415,16 @@
pages = {2548--2555},
organization = {IEEE}
}
@ARTICLE{Louhichi07,
author = {Louhichi, H. and Fournel, T. and Lavest, J. M. and Ben Aissia, H.},
title = {Self-calibration of Scheimpflug cameras: an easy protocol},
year = {2007},
pages = {2616–2622},
journal = {Meas. Sci. Technol.},
volume = {18},
number = {8},
publisher = {IOP Publishing Ltd}
}
@ARTICLE{LibSVM,
author = {Chang, Chih-Chung and Lin, Chih-Jen},
title = {LIBSVM: a library for support vector machines},
......
modules/calib3d/include/opencv2/calib3d.hpp
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modules/calib3d/include/opencv2/calib3d/calib3d_c.h
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......@@ -243,6 +243,8 @@ CVAPI(void) cvDrawChessboardCorners( CvArr* image, CvSize pattern_size,
#define CV_CALIB_RATIONAL_MODEL 16384
#define CV_CALIB_THIN_PRISM_MODEL 32768
#define CV_CALIB_FIX_S1_S2_S3_S4 65536
#define CV_CALIB_TILTED_MODEL 262144
#define CV_CALIB_FIX_TAUX_TAUY 524288
/* Finds intrinsic and extrinsic camera parameters
......
modules/calib3d/src/calibration.cpp
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modules/calib3d/test/test_cameracalibration_tilt.cpp 0 → 100644
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modules/core/include/opencv2/core/matx.hpp
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......@@ -114,6 +114,10 @@ public:
Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
_Tp v4, _Tp v5, _Tp v6, _Tp v7,
_Tp v8, _Tp v9, _Tp v10, _Tp v11); //!< 1x12, 2x6, 3x4, 4x3, 6x2 or 12x1 matrix
Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
_Tp v4, _Tp v5, _Tp v6, _Tp v7,
_Tp v8, _Tp v9, _Tp v10, _Tp v11,
_Tp v12, _Tp v13); //!< 1x14, 2x7, 7x2 or 14x1 matrix
Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
_Tp v4, _Tp v5, _Tp v6, _Tp v7,
_Tp v8, _Tp v9, _Tp v10, _Tp v11,
......@@ -319,6 +323,7 @@ public:
Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7); //!< 8-element vector constructor
Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8); //!< 9-element vector constructor
Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9); //!< 10-element vector constructor
Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13); //!< 14-element vector constructor
explicit Vec(const _Tp* values);
Vec(const Vec<_Tp, cn>& v);
......@@ -581,6 +586,17 @@ Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp
for(int i = 12; i < channels; i++) val[i] = _Tp(0);
}
template<typename _Tp, int m, int n> inline
Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13)
{
CV_StaticAssert(channels == 14, "Matx should have at least 14 elements.");
val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11;
val[12] = v12; val[13] = v13;
}
template<typename _Tp, int m, int n> inline
Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13, _Tp v14, _Tp v15)
{
......@@ -931,6 +947,10 @@ template<typename _Tp, int cn> inline
Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9)
: Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9) {}
template<typename _Tp, int cn> inline
Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13)
: Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13) {}
template<typename _Tp, int cn> inline
Vec<_Tp, cn>::Vec(const _Tp* values)
: Matx<_Tp, cn, 1>(values) {}
......
modules/imgproc/include/opencv2/imgproc.hpp
View file @ 6882c10b
......@@ -2598,8 +2598,8 @@ the same.
@param dst Output (corrected) image that has the same size and type as src .
@param cameraMatrix Input camera matrix \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
@param distCoeffs Input vector of distortion coefficients
\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]])\f$ of 4, 5, or 8 elements. If the vector is
NULL/empty, the zero distortion coefficients are assumed.
\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
@param newCameraMatrix Camera matrix of the distorted image. By default, it is the same as
cameraMatrix but you may additionally scale and shift the result by using a different matrix.
*/
......@@ -2625,8 +2625,28 @@ The function actually builds the maps for the inverse mapping algorithm that is
is, for each pixel \f$(u, v)\f$ in the destination (corrected and rectified) image, the function
computes the corresponding coordinates in the source image (that is, in the original image from
camera). The following process is applied:
\f[\begin{array}{l} x \leftarrow (u - {c'}_x)/{f'}_x \\ y \leftarrow (v - {c'}_y)/{f'}_y \\{[X\,Y\,W]} ^T \leftarrow R^{-1}*[x \, y \, 1]^T \\ x' \leftarrow X/W \\ y' \leftarrow Y/W \\ x" \leftarrow x' (1 + k_1 r^2 + k_2 r^4 + k_3 r^6) + 2p_1 x' y' + p_2(r^2 + 2 x'^2) \\ y" \leftarrow y' (1 + k_1 r^2 + k_2 r^4 + k_3 r^6) + p_1 (r^2 + 2 y'^2) + 2 p_2 x' y' \\ map_x(u,v) \leftarrow x" f_x + c_x \\ map_y(u,v) \leftarrow y" f_y + c_y \end{array}\f]
where \f$(k_1, k_2, p_1, p_2[, k_3])\f$ are the distortion coefficients.
\f[
\begin{array}{l}
x \leftarrow (u - {c'}_x)/{f'}_x \\
y \leftarrow (v - {c'}_y)/{f'}_y \\
{[X\,Y\,W]} ^T \leftarrow R^{-1}*[x \, y \, 1]^T \\
x' \leftarrow X/W \\
y' \leftarrow Y/W \\
r^2 \leftarrow x'^2 + y'^2 \\
x'' \leftarrow x' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6}
+ 2p_1 x' y' + p_2(r^2 + 2 x'^2) + s_1 r^2 + s_2 r^4\\
y'' \leftarrow y' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6}
+ p_1 (r^2 + 2 y'^2) + 2 p_2 x' y' + s_3 r^2 + s_4 r^4 \\
s\vecthree{x'''}{y'''}{1} =
\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}((\tau_x, \tau_y)}
{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)}
{0}{0}{1} R(\tau_x, \tau_y) \vecthree{x''}{y''}{1}\\
map_x(u,v) \leftarrow x''' f_x + c_x \\
map_y(u,v) \leftarrow y''' f_y + c_y
\end{array}
\f]
where \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
are the distortion coefficients.
In case of a stereo camera, this function is called twice: once for each camera head, after
stereoRectify, which in its turn is called after cv::stereoCalibrate. But if the stereo camera
......@@ -2639,8 +2659,8 @@ where cameraMatrix can be chosen arbitrarily.
@param cameraMatrix Input camera matrix \f$A=\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
@param distCoeffs Input vector of distortion coefficients
\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]])\f$ of 4, 5, or 8 elements. If the vector is
NULL/empty, the zero distortion coefficients are assumed.
\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
@param R Optional rectification transformation in the object space (3x3 matrix). R1 or R2 ,
computed by stereoRectify can be passed here. If the matrix is empty, the identity transformation
is assumed. In cvInitUndistortMap R assumed to be an identity matrix.
......@@ -2715,8 +2735,8 @@ The function can be used for both a stereo camera head or a monocular camera (wh
transformation. If matrix P is identity or omitted, dst will contain normalized point coordinates.
@param cameraMatrix Camera matrix \f$\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
@param distCoeffs Input vector of distortion coefficients
\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]])\f$ of 4, 5, or 8 elements. If the vector is
NULL/empty, the zero distortion coefficients are assumed.
\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
@param R Rectification transformation in the object space (3x3 matrix). R1 or R2 computed by
cv::stereoRectify can be passed here. If the matrix is empty, the identity transformation is used.
@param P New camera matrix (3x3) or new projection matrix (3x4). P1 or P2 computed by
......
modules/imgproc/include/opencv2/imgproc/detail/distortion_model.hpp 0 → 100644
View file @ 6882c10b
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// 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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, 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.
//
// * The name of the copyright holders may not 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 Intel Corporation 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.
//
//M*/
#ifndef __OPENCV_IMGPROC_DETAIL_DISTORTION_MODEL_HPP__
#define __OPENCV_IMGPROC_DETAIL_DISTORTION_MODEL_HPP__
//! @cond IGNORED
namespace cv { namespace detail {
/**
Computes the matrix for the projection onto a tilted image sensor
\param tauX angular parameter rotation around x-axis
\param tauY angular parameter rotation around y-axis
\param matTilt if not NULL returns the matrix
\f[
\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}((\tau_x, \tau_y)}
{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)}
{0}{0}{1} R(\tau_x, \tau_y)
\f]
where
\f[
R(\tau_x, \tau_y) =
\vecthreethree{\cos(\tau_y)}{0}{-\sin(\tau_y)}{0}{1}{0}{\sin(\tau_y)}{0}{\cos(\tau_y)}
\vecthreethree{1}{0}{0}{0}{\cos(\tau_x)}{\sin(\tau_x)}{0}{-\sin(\tau_x)}{\cos(\tau_x)} =
\vecthreethree{\cos(\tau_y)}{\sin(\tau_y)\sin(\tau_x)}{-\sin(\tau_y)\cos(\tau_x)}
{0}{\cos(\tau_x)}{\sin(\tau_x)}
{\sin(\tau_y)}{-\cos(\tau_y)\sin(\tau_x)}{\cos(\tau_y)\cos(\tau_x)}.
\f]
\param dMatTiltdTauX if not NULL it returns the derivative of matTilt with
respect to \f$\tau_x\f$.
\param dMatTiltdTauY if not NULL it returns the derivative of matTilt with
respect to \f$\tau_y\f$.
\param invMatTilt if not NULL it returns the inverse of matTilt
**/
template <typename FLOAT>
void computeTiltProjectionMatrix(FLOAT tauX,
FLOAT tauY,
Matx<FLOAT, 3, 3>* matTilt = 0,
Matx<FLOAT, 3, 3>* dMatTiltdTauX = 0,
Matx<FLOAT, 3, 3>* dMatTiltdTauY = 0,
Matx<FLOAT, 3, 3>* invMatTilt = 0)
{
FLOAT cTauX = cos(tauX);
FLOAT sTauX = sin(tauX);
FLOAT cTauY = cos(tauY);
FLOAT sTauY = sin(tauY);
Matx<FLOAT, 3, 3> matRotX = Matx<FLOAT, 3, 3>(1,0,0,0,cTauX,sTauX,0,-sTauX,cTauX);
Matx<FLOAT, 3, 3> matRotY = Matx<FLOAT, 3, 3>(cTauY,0,-sTauY,0,1,0,sTauY,0,cTauY);
Matx<FLOAT, 3, 3> matRotXY = matRotY * matRotX;
Matx<FLOAT, 3, 3> matProjZ = Matx<FLOAT, 3, 3>(matRotXY(2,2),0,-matRotXY(0,2),0,matRotXY(2,2),-matRotXY(1,2),0,0,1);
if (matTilt)
{
// Matrix for trapezoidal distortion of tilted image sensor
*matTilt = matProjZ * matRotXY;
}
if (dMatTiltdTauX)
{
// Derivative with respect to tauX
Matx<FLOAT, 3, 3> dMatRotXYdTauX = matRotY * Matx<FLOAT, 3, 3>(0,0,0,0,-sTauX,cTauX,0,-cTauX,-sTauX);
Matx<FLOAT, 3, 3> dMatProjZdTauX = Matx<FLOAT, 3, 3>(dMatRotXYdTauX(2,2),0,-dMatRotXYdTauX(0,2),
0,dMatRotXYdTauX(2,2),-dMatRotXYdTauX(1,2),0,0,0);
*dMatTiltdTauX = (matProjZ * dMatRotXYdTauX) + (dMatProjZdTauX * matRotXY);
}
if (dMatTiltdTauY)
{
// Derivative with respect to tauY
Matx<FLOAT, 3, 3> dMatRotXYdTauY = Matx<FLOAT, 3, 3>(-sTauY,0,-cTauY,0,0,0,cTauY,0,-sTauY) * matRotX;
Matx<FLOAT, 3, 3> dMatProjZdTauY = Matx<FLOAT, 3, 3>(dMatRotXYdTauY(2,2),0,-dMatRotXYdTauY(0,2),
0,dMatRotXYdTauY(2,2),-dMatRotXYdTauY(1,2),0,0,0);
*dMatTiltdTauY = (matProjZ * dMatRotXYdTauY) + (dMatProjZdTauY * matRotXY);
}
if (invMatTilt)
{
FLOAT inv = 1./matRotXY(2,2);
Matx<FLOAT, 3, 3> invMatProjZ = Matx<FLOAT, 3, 3>(inv,0,inv*matRotXY(0,2),0,inv,inv*matRotXY(1,2),0,0,1);
*invMatTilt = matRotXY.t()*invMatProjZ;
}
}
}} // namespace detail, cv
//! @endcond
#endif // __OPENCV_IMGPROC_DETAIL_DISTORTION_MODEL_HPP__
modules/imgproc/src/undistort.cpp
View file @ 6882c10b
......@@ -41,6 +41,7 @@
//M*/
#include "precomp.hpp"
#include "opencv2/imgproc/detail/distortion_model.hpp"
cv::Mat cv::getDefaultNewCameraMatrix( InputArray _cameraMatrix, Size imgsize,
bool centerPrincipalPoint )
......@@ -94,7 +95,7 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
distCoeffs = Mat_<double>(distCoeffs);
else
{
distCoeffs.create(12, 1, CV_64F);
distCoeffs.create(14, 1, CV_64F);
distCoeffs = 0.;
}
......@@ -109,7 +110,8 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
CV_Assert( distCoeffs.size() == Size(1, 4) || distCoeffs.size() == Size(4, 1) ||
distCoeffs.size() == Size(1, 5) || distCoeffs.size() == Size(5, 1) ||
distCoeffs.size() == Size(1, 8) || distCoeffs.size() == Size(8, 1) ||
distCoeffs.size() == Size(1, 12) || distCoeffs.size() == Size(12, 1));
distCoeffs.size() == Size(1, 12) || distCoeffs.size() == Size(12, 1) ||
distCoeffs.size() == Size(1, 14) || distCoeffs.size() == Size(14, 1));
if( distCoeffs.rows != 1 && !distCoeffs.isContinuous() )
distCoeffs = distCoeffs.t();
......@@ -127,6 +129,12 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
double s2 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[9] : 0.;
double s3 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[10] : 0.;
double s4 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[11] : 0.;
double tauX = distCoeffs.cols + distCoeffs.rows - 1 >= 14 ? distPtr[12] : 0.;
double tauY = distCoeffs.cols + distCoeffs.rows - 1 >= 14 ? distPtr[13] : 0.;
// Matrix for trapezoidal distortion of tilted image sensor
cv::Matx33d matTilt = cv::Matx33d::eye();
cv::detail::computeTiltProjectionMatrix(tauX, tauY, &matTilt);
for( int i = 0; i < size.height; i++ )
{
......@@ -142,8 +150,12 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
double x2 = x*x, y2 = y*y;
double r2 = x2 + y2, _2xy = 2*x*y;
double kr = (1 + ((k3*r2 + k2)*r2 + k1)*r2)/(1 + ((k6*r2 + k5)*r2 + k4)*r2);
double u = fx*(x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+s2*r2*r2) + u0;
double v = fy*(y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+s4*r2*r2) + v0;
double xd = (x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+s2*r2*r2);
double yd = (y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+s4*r2*r2);
cv::Vec3d vecTilt = matTilt*cv::Vec3d(xd, yd, 1);
double invProj = vecTilt(2) ? 1./vecTilt(2) : 1;
double u = fx*invProj*vecTilt(0) + u0;
double v = fy*invProj*vecTilt(1) + v0;
if( m1type == CV_16SC2 )
{
int iu = saturate_cast<int>(u*INTER_TAB_SIZE);
......@@ -266,7 +278,7 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
const CvMat* _distCoeffs,
const CvMat* matR, const CvMat* matP )
{
double A[3][3], RR[3][3], k[12]={0,0,0,0,0,0,0,0,0,0,0}, fx, fy, ifx, ify, cx, cy;
double A[3][3], RR[3][3], k[14]={0,0,0,0,0,0,0,0,0,0,0,0,0,0}, fx, fy, ifx, ify, cx, cy;
CvMat matA=cvMat(3, 3, CV_64F, A), _Dk;
CvMat _RR=cvMat(3, 3, CV_64F, RR);
const CvPoint2D32f* srcf;
......@@ -276,6 +288,7 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
int stype, dtype;
int sstep, dstep;
int i, j, n, iters = 1;
cv::Matx33d invMatTilt = cv::Matx33d::eye();
CV_Assert( CV_IS_MAT(_src) && CV_IS_MAT(_dst) &&
(_src->rows == 1 || _src->cols == 1) &&
......@@ -296,13 +309,16 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
(_distCoeffs->rows*_distCoeffs->cols == 4 ||
_distCoeffs->rows*_distCoeffs->cols == 5 ||
_distCoeffs->rows*_distCoeffs->cols == 8 ||
_distCoeffs->rows*_distCoeffs->cols == 12));
_distCoeffs->rows*_distCoeffs->cols == 12 ||
_distCoeffs->rows*_distCoeffs->cols == 14));
_Dk = cvMat( _distCoeffs->rows, _distCoeffs->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(_distCoeffs->type)), k);
cvConvert( _distCoeffs, &_Dk );
iters = 5;
if (k[12] != 0 || k[13] != 0)
cv::detail::computeTiltProjectionMatrix<double>(k[12], k[13], NULL, NULL, NULL, &invMatTilt);
}
if( matR )
......@@ -354,8 +370,14 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
y = srcd[i*sstep].y;
}
x0 = x = (x - cx)*ifx;
y0 = y = (y - cy)*ify;
x = (x - cx)*ifx;
y = (y - cy)*ify;
// compensate tilt distortion
cv::Vec3d vecUntilt = invMatTilt * cv::Vec3d(x, y, 1);
double invProj = vecUntilt(2) ? 1./vecUntilt(2) : 1;
x0 = x = invProj * vecUntilt(0);
y0 = y = invProj * vecUntilt(1);
// compensate distortion iteratively
for( j = 0; j < iters; j++ )
......@@ -500,7 +522,7 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
OutputArray _map1, OutputArray _map2, int projType, double _alpha )
{
Mat cameraMatrix0 = _cameraMatrix0.getMat(), distCoeffs0 = _distCoeffs0.getMat();
double k[12] = {0,0,0,0,0,0,0,0,0,0,0}, M[9]={0,0,0,0,0,0,0,0,0};
double k[14] = {0,0,0,0,0,0,0,0,0,0,0,0,0,0}, M[9]={0,0,0,0,0,0,0,0,0};
Mat distCoeffs(distCoeffs0.rows, distCoeffs0.cols, CV_MAKETYPE(CV_64F,distCoeffs0.channels()), k);
Mat cameraMatrix(3,3,CV_64F,M);
Point2f scenter((float)cameraMatrix.at<double>(0,2), (float)cameraMatrix.at<double>(1,2));
......@@ -513,7 +535,7 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
int ndcoeffs = distCoeffs0.cols*distCoeffs0.rows*distCoeffs0.channels();
CV_Assert((distCoeffs0.cols == 1 || distCoeffs0.rows == 1) &&
(ndcoeffs == 4 || ndcoeffs == 5 || ndcoeffs == 8));
(ndcoeffs == 4 || ndcoeffs == 5 || ndcoeffs == 8 || ndcoeffs == 12 || ndcoeffs == 14));
CV_Assert(cameraMatrix0.size() == Size(3,3));
distCoeffs0.convertTo(distCoeffs,CV_64F);
cameraMatrix0.convertTo(cameraMatrix,CV_64F);
......@@ -540,6 +562,8 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
Mat mapxy(dsize, CV_32FC2);
double k1 = k[0], k2 = k[1], k3 = k[2], p1 = k[3], p2 = k[4], k4 = k[5], k5 = k[6], k6 = k[7], s1 = k[8], s2 = k[9], s3 = k[10], s4 = k[11];
double fx = cameraMatrix.at<double>(0,0), fy = cameraMatrix.at<double>(1,1), cx = scenter.x, cy = scenter.y;
cv::Matx33d matTilt;
cv::detail::computeTiltProjectionMatrix(k[12], k[13], &matTilt);
for( int y = 0; y < dsize.height; y++ )
{
......@@ -556,8 +580,12 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
double x2 = q.x*q.x, y2 = q.y*q.y;
double r2 = x2 + y2, _2xy = 2*q.x*q.y;
double kr = 1 + ((k3*r2 + k2)*r2 + k1)*r2/(1 + ((k6*r2 + k5)*r2 + k4)*r2);
double u = fx*(q.x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+ s2*r2*r2) + cx;
double v = fy*(q.y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+ s4*r2*r2) + cy;
double xd = (q.x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+ s2*r2*r2);
double yd = (q.y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+ s4*r2*r2);
cv::Vec3d vecTilt = matTilt*cv::Vec3d(xd, yd, 1);
double invProj = vecTilt(2) ? 1./vecTilt(2) : 1;
double u = fx*invProj*vecTilt(0) + cx;
double v = fy*invProj*vecTilt(1) + cy;
mxy[x] = Point2f((float)u, (float)v);
}
......
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