Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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#include "precomp.hpp"
#define SHOW_DEBUG_IMAGES 0
#include "opencv2/core/core.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#if SHOW_DEBUG_IMAGES
# include "opencv2/highgui/highgui.hpp"
#endif
#include <iostream>
#include <limits>
#include "opencv2/core/internal.hpp"
#if defined(HAVE_EIGEN) && EIGEN_WORLD_VERSION == 3
# ifdef ANDROID
template <typename Scalar> Scalar log2(Scalar v) { using std::log; return log(v)/log(Scalar(2)); }
# endif
# include <unsupported/Eigen/MatrixFunctions>
# include <Eigen/Dense>
#endif
using namespace cv;
inline static
void computeC_RigidBodyMotion( double* C, double dIdx, double dIdy, const Point3f& p3d, double fx, double fy )
{
double invz = 1. / p3d.z,
v0 = dIdx * fx * invz,
v1 = dIdy * fy * invz,
v2 = -(v0 * p3d.x + v1 * p3d.y) * invz;
C[0] = -p3d.z * v1 + p3d.y * v2;
C[1] = p3d.z * v0 - p3d.x * v2;
C[2] = -p3d.y * v0 + p3d.x * v1;
C[3] = v0;
C[4] = v1;
C[5] = v2;
}
inline static
void computeC_Rotation( double* C, double dIdx, double dIdy, const Point3f& p3d, double fx, double fy )
{
double invz = 1. / p3d.z,
v0 = dIdx * fx * invz,
v1 = dIdy * fy * invz,
v2 = -(v0 * p3d.x + v1 * p3d.y) * invz;
C[0] = -p3d.z * v1 + p3d.y * v2;
C[1] = p3d.z * v0 - p3d.x * v2;
C[2] = -p3d.y * v0 + p3d.x * v1;
}
inline static
void computeC_Translation( double* C, double dIdx, double dIdy, const Point3f& p3d, double fx, double fy )
{
double invz = 1. / p3d.z,
v0 = dIdx * fx * invz,
v1 = dIdy * fy * invz,
v2 = -(v0 * p3d.x + v1 * p3d.y) * invz;
C[0] = v0;
C[1] = v1;
C[2] = v2;
}
inline static
void computeProjectiveMatrix( const Mat& ksi, Mat& Rt )
{
CV_Assert( ksi.size() == Size(1,6) && ksi.type() == CV_64FC1 );
#if defined(HAVE_EIGEN) && EIGEN_WORLD_VERSION == 3
const double* ksi_ptr = reinterpret_cast<const double*>(ksi.ptr(0));
Eigen::Matrix<double,4,4> twist, g;
twist << 0., -ksi_ptr[2], ksi_ptr[1], ksi_ptr[3],
ksi_ptr[2], 0., -ksi_ptr[0], ksi_ptr[4],
-ksi_ptr[1], ksi_ptr[0], 0, ksi_ptr[5],
0., 0., 0., 0.;
g = twist.exp();
eigen2cv(g, Rt);
#else
// for infinitesimal transformation
Rt = Mat::eye(4, 4, CV_64FC1);
Mat R = Rt(Rect(0,0,3,3));
Mat rvec = ksi.rowRange(0,3);
Rodrigues( rvec, R );
Rt.at<double>(0,3) = ksi.at<double>(3);
Rt.at<double>(1,3) = ksi.at<double>(4);
Rt.at<double>(2,3) = ksi.at<double>(5);
#endif
}
static
void cvtDepth2Cloud( const Mat& depth, Mat& cloud, const Mat& cameraMatrix )
{
CV_Assert( cameraMatrix.type() == CV_64FC1 );
const double inv_fx = 1.f/cameraMatrix.at<double>(0,0);
const double inv_fy = 1.f/cameraMatrix.at<double>(1,1);
const double ox = cameraMatrix.at<double>(0,2);
const double oy = cameraMatrix.at<double>(1,2);
cloud.create( depth.size(), CV_32FC3 );
for( int y = 0; y < cloud.rows; y++ )
{
Point3f* cloud_ptr = reinterpret_cast<Point3f*>(cloud.ptr(y));
const float* depth_prt = reinterpret_cast<const float*>(depth.ptr(y));
for( int x = 0; x < cloud.cols; x++ )
{
float z = depth_prt[x];
cloud_ptr[x].x = (float)((x - ox) * z * inv_fx);
cloud_ptr[x].y = (float)((y - oy) * z * inv_fy);
cloud_ptr[x].z = z;
}
}
}
#if SHOW_DEBUG_IMAGES
template<class ImageElemType>
static void warpImage( const Mat& image, const Mat& depth,
const Mat& Rt, const Mat& cameraMatrix, const Mat& distCoeff,
Mat& warpedImage )
{
const Rect rect = Rect(0, 0, image.cols, image.rows);
vector<Point2f> points2d;
Mat cloud, transformedCloud;
cvtDepth2Cloud( depth, cloud, cameraMatrix );
perspectiveTransform( cloud, transformedCloud, Rt );
projectPoints( transformedCloud.reshape(3,1), Mat::eye(3,3,CV_64FC1), Mat::zeros(3,1,CV_64FC1), cameraMatrix, distCoeff, points2d );
Mat pointsPositions( points2d );
pointsPositions = pointsPositions.reshape( 2, image.rows );
warpedImage.create( image.size(), image.type() );
warpedImage = Scalar::all(0);
Mat zBuffer( image.size(), CV_32FC1, FLT_MAX );
for( int y = 0; y < image.rows; y++ )
{
for( int x = 0; x < image.cols; x++ )
{
const Point3f p3d = transformedCloud.at<Point3f>(y,x);
const Point p2d = pointsPositions.at<Point2f>(y,x);
if( !cvIsNaN(cloud.at<Point3f>(y,x).z) && cloud.at<Point3f>(y,x).z > 0 &&
rect.contains(p2d) && zBuffer.at<float>(p2d) > p3d.z )
{
warpedImage.at<ImageElemType>(p2d) = image.at<ImageElemType>(y,x);
zBuffer.at<float>(p2d) = p3d.z;
}
}
}
}
#endif
static inline
void set2shorts( int& dst, int short_v1, int short_v2 )
{
unsigned short* ptr = reinterpret_cast<unsigned short*>(&dst);
ptr[0] = static_cast<unsigned short>(short_v1);
ptr[1] = static_cast<unsigned short>(short_v2);
}
static inline
void get2shorts( int src, int& short_v1, int& short_v2 )
{
typedef union { int vint32; unsigned short vuint16[2]; } s32tou16;
const unsigned short* ptr = (reinterpret_cast<s32tou16*>(&src))->vuint16;
short_v1 = ptr[0];
short_v2 = ptr[1];
}
static
int computeCorresp( const Mat& K, const Mat& K_inv, const Mat& Rt,
const Mat& depth0, const Mat& depth1, const Mat& texturedMask1, float maxDepthDiff,
Mat& corresps )
{
CV_Assert( K.type() == CV_64FC1 );
CV_Assert( K_inv.type() == CV_64FC1 );
CV_Assert( Rt.type() == CV_64FC1 );
corresps.create( depth1.size(), CV_32SC1 );
Mat R = Rt(Rect(0,0,3,3)).clone();
Mat KRK_inv = K * R * K_inv;
const double * KRK_inv_ptr = reinterpret_cast<const double *>(KRK_inv.ptr());
Mat Kt = Rt(Rect(3,0,1,3)).clone();
Kt = K * Kt;
const double * Kt_ptr = reinterpret_cast<const double *>(Kt.ptr());
Rect r(0, 0, depth1.cols, depth1.rows);
corresps = Scalar(-1);
int correspCount = 0;
for( int v1 = 0; v1 < depth1.rows; v1++ )
{
for( int u1 = 0; u1 < depth1.cols; u1++ )
{
float d1 = depth1.at<float>(v1,u1);
if( !cvIsNaN(d1) && texturedMask1.at<uchar>(v1,u1) )
{
float transformed_d1 = (float)(d1 * (KRK_inv_ptr[6] * u1 + KRK_inv_ptr[7] * v1 + KRK_inv_ptr[8]) + Kt_ptr[2]);
int u0 = cvRound((d1 * (KRK_inv_ptr[0] * u1 + KRK_inv_ptr[1] * v1 + KRK_inv_ptr[2]) + Kt_ptr[0]) / transformed_d1);
int v0 = cvRound((d1 * (KRK_inv_ptr[3] * u1 + KRK_inv_ptr[4] * v1 + KRK_inv_ptr[5]) + Kt_ptr[1]) / transformed_d1);
if( r.contains(Point(u0,v0)) )
{
float d0 = depth0.at<float>(v0,u0);
if( !cvIsNaN(d0) && std::abs(transformed_d1 - d0) <= maxDepthDiff )
{
int c = corresps.at<int>(v0,u0);
if( c != -1 )
{
int exist_u1, exist_v1;
get2shorts( c, exist_u1, exist_v1);
float exist_d1 = (float)(depth1.at<float>(exist_v1,exist_u1) * (KRK_inv_ptr[6] * exist_u1 + KRK_inv_ptr[7] * exist_v1 + KRK_inv_ptr[8]) + Kt_ptr[2]);
if( transformed_d1 > exist_d1 )
continue;
}
else
correspCount++;
set2shorts( corresps.at<int>(v0,u0), u1, v1 );
}
}
}
}
}
return correspCount;
}
static inline
void preprocessDepth( Mat depth0, Mat depth1,
const Mat& validMask0, const Mat& validMask1,
float minDepth, float maxDepth )
{
CV_DbgAssert( depth0.size() == depth1.size() );
for( int y = 0; y < depth0.rows; y++ )
{
for( int x = 0; x < depth0.cols; x++ )
{
float& d0 = depth0.at<float>(y,x);
if( !cvIsNaN(d0) && (d0 > maxDepth || d0 < minDepth || d0 <= 0 || (!validMask0.empty() && !validMask0.at<uchar>(y,x))) )
d0 = std::numeric_limits<float>::quiet_NaN();
float& d1 = depth1.at<float>(y,x);
if( !cvIsNaN(d1) && (d1 > maxDepth || d1 < minDepth || d1 <= 0 || (!validMask1.empty() && !validMask1.at<uchar>(y,x))) )
d1 = std::numeric_limits<float>::quiet_NaN();
}
}
}
static
void buildPyramids( const Mat& image0, const Mat& image1,
const Mat& depth0, const Mat& depth1,
const Mat& cameraMatrix, int sobelSize, double sobelScale,
const vector<float>& minGradMagnitudes,
vector<Mat>& pyramidImage0, vector<Mat>& pyramidDepth0,
vector<Mat>& pyramidImage1, vector<Mat>& pyramidDepth1,
vector<Mat>& pyramid_dI_dx1, vector<Mat>& pyramid_dI_dy1,
vector<Mat>& pyramidTexturedMask1, vector<Mat>& pyramidCameraMatrix )
{
const int pyramidMaxLevel = (int)minGradMagnitudes.size() - 1;
buildPyramid( image0, pyramidImage0, pyramidMaxLevel );
buildPyramid( image1, pyramidImage1, pyramidMaxLevel );
pyramid_dI_dx1.resize( pyramidImage1.size() );
pyramid_dI_dy1.resize( pyramidImage1.size() );
pyramidTexturedMask1.resize( pyramidImage1.size() );
pyramidCameraMatrix.reserve( pyramidImage1.size() );
Mat cameraMatrix_dbl;
cameraMatrix.convertTo( cameraMatrix_dbl, CV_64FC1 );
for( size_t i = 0; i < pyramidImage1.size(); i++ )
{
Sobel( pyramidImage1[i], pyramid_dI_dx1[i], CV_16S, 1, 0, sobelSize );
Sobel( pyramidImage1[i], pyramid_dI_dy1[i], CV_16S, 0, 1, sobelSize );
const Mat& dx = pyramid_dI_dx1[i];
const Mat& dy = pyramid_dI_dy1[i];
Mat texturedMask( dx.size(), CV_8UC1, Scalar(0) );
const float minScalesGradMagnitude2 = (float)((minGradMagnitudes[i] * minGradMagnitudes[i]) / (sobelScale * sobelScale));
for( int y = 0; y < dx.rows; y++ )
{
for( int x = 0; x < dx.cols; x++ )
{
float m2 = (float)(dx.at<short>(y,x)*dx.at<short>(y,x) + dy.at<short>(y,x)*dy.at<short>(y,x));
if( m2 >= minScalesGradMagnitude2 )
texturedMask.at<uchar>(y,x) = 255;
}
}
pyramidTexturedMask1[i] = texturedMask;
Mat levelCameraMatrix = i == 0 ? cameraMatrix_dbl : 0.5f * pyramidCameraMatrix[i-1];
levelCameraMatrix.at<double>(2,2) = 1.;
pyramidCameraMatrix.push_back( levelCameraMatrix );
}
buildPyramid( depth0, pyramidDepth0, pyramidMaxLevel );
buildPyramid( depth1, pyramidDepth1, pyramidMaxLevel );
}
static
bool solveSystem( const Mat& C, const Mat& dI_dt, double detThreshold, Mat& ksi )
{
#if defined(HAVE_EIGEN) && EIGEN_WORLD_VERSION == 3
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> eC, eCt, edI_dt;
cv2eigen(C, eC);
cv2eigen(dI_dt, edI_dt);
eCt = eC.transpose();
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> A, B, eksi;
A = eCt * eC;
double det = A.determinant();
if( fabs (det) < detThreshold || cvIsNaN(det) || cvIsInf(det) )
return false;
B = -eCt * edI_dt;
eksi = A.ldlt().solve(B);
eigen2cv( eksi, ksi );
#else
Mat A = C.t() * C;
double det = cv::determinant(A);
if( fabs (det) < detThreshold || cvIsNaN(det) || cvIsInf(det) )
return false;
Mat B = -C.t() * dI_dt;
cv::solve( A, B, ksi, DECOMP_CHOLESKY );
#endif
return true;
}
typedef void (*ComputeCFuncPtr)( double* C, double dIdx, double dIdy, const Point3f& p3d, double fx, double fy );
static
bool computeKsi( int transformType,
const Mat& image0, const Mat& cloud0,
const Mat& image1, const Mat& dI_dx1, const Mat& dI_dy1,
const Mat& corresps, int correspsCount,
double fx, double fy, double sobelScale, double determinantThreshold,
Mat& ksi )
{
int Cwidth = -1;
ComputeCFuncPtr computeCFuncPtr = 0;
if( transformType == RIGID_BODY_MOTION )
{
Cwidth = 6;
computeCFuncPtr = computeC_RigidBodyMotion;
}
else if( transformType == ROTATION )
{
Cwidth = 3;
computeCFuncPtr = computeC_Rotation;
}
else if( transformType == TRANSLATION )
{
Cwidth = 3;
computeCFuncPtr = computeC_Translation;
}
else
CV_Error( CV_StsBadFlag, "Unsupported value of transformation type flag.");
Mat C( correspsCount, Cwidth, CV_64FC1 );
Mat dI_dt( correspsCount, 1, CV_64FC1 );
double sigma = 0;
int pointCount = 0;
for( int v0 = 0; v0 < corresps.rows; v0++ )
{
for( int u0 = 0; u0 < corresps.cols; u0++ )
{
if( corresps.at<int>(v0,u0) != -1 )
{
int u1, v1;
get2shorts( corresps.at<int>(v0,u0), u1, v1 );
double diff = static_cast<double>(image1.at<uchar>(v1,u1)) -
static_cast<double>(image0.at<uchar>(v0,u0));
sigma += diff * diff;
pointCount++;
}
}
}
sigma = std::sqrt(sigma/pointCount);
pointCount = 0;
for( int v0 = 0; v0 < corresps.rows; v0++ )
{
for( int u0 = 0; u0 < corresps.cols; u0++ )
{
if( corresps.at<int>(v0,u0) != -1 )
{
int u1, v1;
get2shorts( corresps.at<int>(v0,u0), u1, v1 );
double diff = static_cast<double>(image1.at<uchar>(v1,u1)) -
static_cast<double>(image0.at<uchar>(v0,u0));
double w = sigma + std::abs(diff);
w = w > DBL_EPSILON ? 1./w : 1.;
(*computeCFuncPtr)( (double*)C.ptr(pointCount),
w * sobelScale * dI_dx1.at<short int>(v1,u1),
w * sobelScale * dI_dy1.at<short int>(v1,u1),
cloud0.at<Point3f>(v0,u0), fx, fy);
dI_dt.at<double>(pointCount) = w * diff;
pointCount++;
}
}
}
Mat sln;
bool solutionExist = solveSystem( C, dI_dt, determinantThreshold, sln );
if( solutionExist )
{
ksi.create(6,1,CV_64FC1);
ksi = Scalar(0);
Mat subksi;
if( transformType == RIGID_BODY_MOTION )
{
subksi = ksi;
}
else if( transformType == ROTATION )
{
subksi = ksi.rowRange(0,3);
}
else if( transformType == TRANSLATION )
{
subksi = ksi.rowRange(3,6);
}
sln.copyTo( subksi );
}
return solutionExist;
}
bool cv::RGBDOdometry( cv::Mat& Rt, const Mat& initRt,
const cv::Mat& image0, const cv::Mat& _depth0, const cv::Mat& validMask0,
const cv::Mat& image1, const cv::Mat& _depth1, const cv::Mat& validMask1,
const cv::Mat& cameraMatrix, float minDepth, float maxDepth, float maxDepthDiff,
const std::vector<int>& iterCounts, const std::vector<float>& minGradientMagnitudes,
int transformType )
{
const int sobelSize = 3;
const double sobelScale = 1./8;
Mat depth0 = _depth0.clone(),
depth1 = _depth1.clone();
// check RGB-D input data
CV_Assert( !image0.empty() );
CV_Assert( image0.type() == CV_8UC1 );
CV_Assert( depth0.type() == CV_32FC1 && depth0.size() == image0.size() );
CV_Assert( image1.size() == image0.size() );
CV_Assert( image1.type() == CV_8UC1 );
CV_Assert( depth1.type() == CV_32FC1 && depth1.size() == image0.size() );
// check masks
CV_Assert( validMask0.empty() || (validMask0.type() == CV_8UC1 && validMask0.size() == image0.size()) );
CV_Assert( validMask1.empty() || (validMask1.type() == CV_8UC1 && validMask1.size() == image0.size()) );
// check camera params
CV_Assert( cameraMatrix.type() == CV_32FC1 && cameraMatrix.size() == Size(3,3) );
// other checks
CV_Assert( iterCounts.empty() || minGradientMagnitudes.empty() ||
minGradientMagnitudes.size() == iterCounts.size() );
CV_Assert( initRt.empty() || (initRt.type()==CV_64FC1 && initRt.size()==Size(4,4) ) );
vector<int> defaultIterCounts;
vector<float> defaultMinGradMagnitudes;
vector<int> const* iterCountsPtr = &iterCounts;
vector<float> const* minGradientMagnitudesPtr = &minGradientMagnitudes;
if( iterCounts.empty() || minGradientMagnitudes.empty() )
{
defaultIterCounts.resize(4);
defaultIterCounts[0] = 7;
defaultIterCounts[1] = 7;
defaultIterCounts[2] = 7;
defaultIterCounts[3] = 10;
defaultMinGradMagnitudes.resize(4);
defaultMinGradMagnitudes[0] = 12;
defaultMinGradMagnitudes[1] = 5;
defaultMinGradMagnitudes[2] = 3;
defaultMinGradMagnitudes[3] = 1;
iterCountsPtr = &defaultIterCounts;
minGradientMagnitudesPtr = &defaultMinGradMagnitudes;
}
preprocessDepth( depth0, depth1, validMask0, validMask1, minDepth, maxDepth );
vector<Mat> pyramidImage0, pyramidDepth0,
pyramidImage1, pyramidDepth1, pyramid_dI_dx1, pyramid_dI_dy1, pyramidTexturedMask1,
pyramidCameraMatrix;
buildPyramids( image0, image1, depth0, depth1, cameraMatrix, sobelSize, sobelScale, *minGradientMagnitudesPtr,
pyramidImage0, pyramidDepth0, pyramidImage1, pyramidDepth1,
pyramid_dI_dx1, pyramid_dI_dy1, pyramidTexturedMask1, pyramidCameraMatrix );
Mat resultRt = initRt.empty() ? Mat::eye(4,4,CV_64FC1) : initRt.clone();
Mat currRt, ksi;
for( int level = (int)iterCountsPtr->size() - 1; level >= 0; level-- )
{
const Mat& levelCameraMatrix = pyramidCameraMatrix[level];
const Mat& levelImage0 = pyramidImage0[level];
const Mat& levelDepth0 = pyramidDepth0[level];
Mat levelCloud0;
cvtDepth2Cloud( pyramidDepth0[level], levelCloud0, levelCameraMatrix );
const Mat& levelImage1 = pyramidImage1[level];
const Mat& levelDepth1 = pyramidDepth1[level];
const Mat& level_dI_dx1 = pyramid_dI_dx1[level];
const Mat& level_dI_dy1 = pyramid_dI_dy1[level];
CV_Assert( level_dI_dx1.type() == CV_16S );
CV_Assert( level_dI_dy1.type() == CV_16S );
13 years ago
const double fx = levelCameraMatrix.at<double>(0,0);
const double fy = levelCameraMatrix.at<double>(1,1);
const double determinantThreshold = 1e-6;
13 years ago
Mat corresps( levelImage0.size(), levelImage0.type() );
// Run transformation search on current level iteratively.
for( int iter = 0; iter < (*iterCountsPtr)[level]; iter ++ )
{
int correspsCount = computeCorresp( levelCameraMatrix, levelCameraMatrix.inv(), resultRt.inv(DECOMP_SVD),
levelDepth0, levelDepth1, pyramidTexturedMask1[level], maxDepthDiff,
corresps );
if( correspsCount == 0 )
break;
bool solutionExist = computeKsi( transformType,
levelImage0, levelCloud0,
levelImage1, level_dI_dx1, level_dI_dy1,
corresps, correspsCount,
fx, fy, sobelScale, determinantThreshold,
ksi );
if( !solutionExist )
break;
computeProjectiveMatrix( ksi, currRt );
resultRt = currRt * resultRt;
#if SHOW_DEBUG_IMAGES
std::cout << "currRt " << currRt << std::endl;
Mat warpedImage0;
const Mat distCoeff(1,5,CV_32FC1,Scalar(0));
warpImage<uchar>( levelImage0, levelDepth0, resultRt, levelCameraMatrix, distCoeff, warpedImage0 );
imshow( "im0", levelImage0 );
imshow( "wim0", warpedImage0 );
imshow( "im1", levelImage1 );
waitKey();
#endif
}
}
Rt = resultRt;
return !Rt.empty();
}