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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 @@ ...@@ -415,6 +415,16 @@
pages = {2548--2555}, pages = {2548--2555},
organization = {IEEE} 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, @ARTICLE{LibSVM,
author = {Chang, Chih-Chung and Lin, Chih-Jen}, author = {Chang, Chih-Chung and Lin, Chih-Jen},
title = {LIBSVM: a library for support vector machines}, 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, ...@@ -243,6 +243,8 @@ CVAPI(void) cvDrawChessboardCorners( CvArr* image, CvSize pattern_size,
#define CV_CALIB_RATIONAL_MODEL 16384 #define CV_CALIB_RATIONAL_MODEL 16384
#define CV_CALIB_THIN_PRISM_MODEL 32768 #define CV_CALIB_THIN_PRISM_MODEL 32768
#define CV_CALIB_FIX_S1_S2_S3_S4 65536 #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 /* 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: ...@@ -114,6 +114,10 @@ public:
Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
_Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v4, _Tp v5, _Tp v6, _Tp v7,
_Tp v8, _Tp v9, _Tp v10, _Tp v11); //!< 1x12, 2x6, 3x4, 4x3, 6x2 or 12x1 matrix _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, Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
_Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v4, _Tp v5, _Tp v6, _Tp v7,
_Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v8, _Tp v9, _Tp v10, _Tp v11,
...@@ -319,6 +323,7 @@ public: ...@@ -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); //!< 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); //!< 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); //!< 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); explicit Vec(const _Tp* values);
Vec(const Vec<_Tp, cn>& v); 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 ...@@ -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); 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 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) 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 ...@@ -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) 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) {} : 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 template<typename _Tp, int cn> inline
Vec<_Tp, cn>::Vec(const _Tp* values) Vec<_Tp, cn>::Vec(const _Tp* values)
: Matx<_Tp, cn, 1>(values) {} : Matx<_Tp, cn, 1>(values) {}
......
modules/imgproc/include/opencv2/imgproc.hpp
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...@@ -2598,8 +2598,8 @@ the same. ...@@ -2598,8 +2598,8 @@ the same.
@param dst Output (corrected) image that has the same size and type as src . @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 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 @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 \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
NULL/empty, the zero distortion coefficients are assumed. 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 @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. 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 ...@@ -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 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 computes the corresponding coordinates in the source image (that is, in the original image from
camera). The following process is applied: 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] \f[
where \f$(k_1, k_2, p_1, p_2[, k_3])\f$ are the distortion coefficients. \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 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 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. ...@@ -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 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 @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 \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
NULL/empty, the zero distortion coefficients are assumed. 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 , @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 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. 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 ...@@ -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. 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 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 @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 \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
NULL/empty, the zero distortion coefficients are assumed. 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 @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. 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 @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 @@ ...@@ -41,6 +41,7 @@
//M*/ //M*/
#include "precomp.hpp" #include "precomp.hpp"
#include "opencv2/imgproc/detail/distortion_model.hpp"
cv::Mat cv::getDefaultNewCameraMatrix( InputArray _cameraMatrix, Size imgsize, cv::Mat cv::getDefaultNewCameraMatrix( InputArray _cameraMatrix, Size imgsize,
bool centerPrincipalPoint ) bool centerPrincipalPoint )
...@@ -94,7 +95,7 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef ...@@ -94,7 +95,7 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
distCoeffs = Mat_<double>(distCoeffs); distCoeffs = Mat_<double>(distCoeffs);
else else
{ {
distCoeffs.create(12, 1, CV_64F); distCoeffs.create(14, 1, CV_64F);
distCoeffs = 0.; distCoeffs = 0.;
} }
...@@ -109,7 +110,8 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef ...@@ -109,7 +110,8 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
CV_Assert( distCoeffs.size() == Size(1, 4) || distCoeffs.size() == Size(4, 1) || 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, 5) || distCoeffs.size() == Size(5, 1) ||
distCoeffs.size() == Size(1, 8) || distCoeffs.size() == Size(8, 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() ) if( distCoeffs.rows != 1 && !distCoeffs.isContinuous() )
distCoeffs = distCoeffs.t(); distCoeffs = distCoeffs.t();
...@@ -127,6 +129,12 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef ...@@ -127,6 +129,12 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
double s2 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[9] : 0.; double s2 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[9] : 0.;
double s3 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[10] : 0.; double s3 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[10] : 0.;
double s4 = distCoeffs.cols + distCoeffs.rows - 1 >= 12 ? distPtr[11] : 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++ ) for( int i = 0; i < size.height; i++ )
{ {
...@@ -142,8 +150,12 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef ...@@ -142,8 +150,12 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
double x2 = x*x, y2 = y*y; double x2 = x*x, y2 = y*y;
double r2 = x2 + y2, _2xy = 2*x*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 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 xd = (x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+s2*r2*r2);
double v = fy*(y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+s4*r2*r2) + v0; 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 ) if( m1type == CV_16SC2 )
{ {
int iu = saturate_cast<int>(u*INTER_TAB_SIZE); int iu = saturate_cast<int>(u*INTER_TAB_SIZE);
...@@ -266,7 +278,7 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr ...@@ -266,7 +278,7 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
const CvMat* _distCoeffs, const CvMat* _distCoeffs,
const CvMat* matR, const CvMat* matP ) 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 matA=cvMat(3, 3, CV_64F, A), _Dk;
CvMat _RR=cvMat(3, 3, CV_64F, RR); CvMat _RR=cvMat(3, 3, CV_64F, RR);
const CvPoint2D32f* srcf; const CvPoint2D32f* srcf;
...@@ -276,6 +288,7 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr ...@@ -276,6 +288,7 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
int stype, dtype; int stype, dtype;
int sstep, dstep; int sstep, dstep;
int i, j, n, iters = 1; int i, j, n, iters = 1;
cv::Matx33d invMatTilt = cv::Matx33d::eye();
CV_Assert( CV_IS_MAT(_src) && CV_IS_MAT(_dst) && CV_Assert( CV_IS_MAT(_src) && CV_IS_MAT(_dst) &&
(_src->rows == 1 || _src->cols == 1) && (_src->rows == 1 || _src->cols == 1) &&
...@@ -296,13 +309,16 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr ...@@ -296,13 +309,16 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
(_distCoeffs->rows*_distCoeffs->cols == 4 || (_distCoeffs->rows*_distCoeffs->cols == 4 ||
_distCoeffs->rows*_distCoeffs->cols == 5 || _distCoeffs->rows*_distCoeffs->cols == 5 ||
_distCoeffs->rows*_distCoeffs->cols == 8 || _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, _Dk = cvMat( _distCoeffs->rows, _distCoeffs->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(_distCoeffs->type)), k); CV_MAKETYPE(CV_64F,CV_MAT_CN(_distCoeffs->type)), k);
cvConvert( _distCoeffs, &_Dk ); cvConvert( _distCoeffs, &_Dk );
iters = 5; iters = 5;
if (k[12] != 0 || k[13] != 0)
cv::detail::computeTiltProjectionMatrix<double>(k[12], k[13], NULL, NULL, NULL, &invMatTilt);
} }
if( matR ) if( matR )
...@@ -354,8 +370,14 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr ...@@ -354,8 +370,14 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
y = srcd[i*sstep].y; y = srcd[i*sstep].y;
} }
x0 = x = (x - cx)*ifx; x = (x - cx)*ifx;
y0 = y = (y - cy)*ify; 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 // compensate distortion iteratively
for( j = 0; j < iters; j++ ) for( j = 0; j < iters; j++ )
...@@ -500,7 +522,7 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff ...@@ -500,7 +522,7 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
OutputArray _map1, OutputArray _map2, int projType, double _alpha ) OutputArray _map1, OutputArray _map2, int projType, double _alpha )
{ {
Mat cameraMatrix0 = _cameraMatrix0.getMat(), distCoeffs0 = _distCoeffs0.getMat(); 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 distCoeffs(distCoeffs0.rows, distCoeffs0.cols, CV_MAKETYPE(CV_64F,distCoeffs0.channels()), k);
Mat cameraMatrix(3,3,CV_64F,M); Mat cameraMatrix(3,3,CV_64F,M);
Point2f scenter((float)cameraMatrix.at<double>(0,2), (float)cameraMatrix.at<double>(1,2)); 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 ...@@ -513,7 +535,7 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
int ndcoeffs = distCoeffs0.cols*distCoeffs0.rows*distCoeffs0.channels(); int ndcoeffs = distCoeffs0.cols*distCoeffs0.rows*distCoeffs0.channels();
CV_Assert((distCoeffs0.cols == 1 || distCoeffs0.rows == 1) && 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)); CV_Assert(cameraMatrix0.size() == Size(3,3));
distCoeffs0.convertTo(distCoeffs,CV_64F); distCoeffs0.convertTo(distCoeffs,CV_64F);
cameraMatrix0.convertTo(cameraMatrix,CV_64F); cameraMatrix0.convertTo(cameraMatrix,CV_64F);
...@@ -540,6 +562,8 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff ...@@ -540,6 +562,8 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
Mat mapxy(dsize, CV_32FC2); 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 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; 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++ ) for( int y = 0; y < dsize.height; y++ )
{ {
...@@ -556,8 +580,12 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff ...@@ -556,8 +580,12 @@ float cv::initWideAngleProjMap( InputArray _cameraMatrix0, InputArray _distCoeff
double x2 = q.x*q.x, y2 = q.y*q.y; double x2 = q.x*q.x, y2 = q.y*q.y;
double r2 = x2 + y2, _2xy = 2*q.x*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 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 xd = (q.x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+ s2*r2*r2);
double v = fy*(q.y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+ s4*r2*r2) + cy; 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); mxy[x] = Point2f((float)u, (float)v);
} }
......
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