Opencv 双目标定之后，校正图像出现错误，求大神指导
左右图像标定结果如下
角点顺序左右图都没错。
可是标定之后，校正的图像如下错误
标定代码如下
void main()
{
Size boardSize;
boardSize.width = 11;
boardSize.height = 8;
vector
bool ok = readStringList("D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/stereo_calib.xml", imagelist);
StereoCalib(imagelist, boardSize, true, true, true);
}
bool Binocular_Calibration::StereoCalib(const vector
{
if (imagelist.size() % 2 != 0)
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return false;
}
const int maxScale = 2;
const float squareSize = 1.f; // Set this to your actual square size
// ARRAY AND VECTOR STORAGE:
vector
vector
Size imageSize;
int i, j, k, nimages = (int)imagelist.size() / 2;
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
vector
for (i = j = 0; i < nimages; i++)
{
for (k = 0; k < 2; k++)
{
const string& filename = imagelist[i * 2 + k];
Mat img = imread(filename, 0);
if (img.empty())
break;
if (imageSize == Size())
imageSize = img.size();
else if (img.size() != imageSize)
{
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
break;
}
bool found = false;
vector
for (int scale = 1; scale <= maxScale; scale++)
{
Mat timg;
if (scale == 1)
timg = img;
else
cv::resize(img, timg, Size(), scale, scale);
found = findChessboardCorners(timg, boardSize, corners,
CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE);
if (found)
{
if (scale > 1)
{
Mat cornersMat(corners);
cornersMat *= 1. / scale;
}
break;
}
}
if (displayCorners)
{
cout << filename << endl;
Mat cimg, cimg1;
cvtColor(img, cimg, COLOR_GRAY2BGR);
drawChessboardCorners(cimg, boardSize, corners, found);
double sf = 640. / MAX(img.rows, img.cols);
cv::resize(cimg, cimg1, Size(), sf, sf);
imshow(filename, cimg1);
char c = (char)waitKey(500);
if (c == 27 || c == 'q' || c == 'Q') //Allow ESC to quit
exit(-1);
}
else
putchar('.');
if (!found)
break;
cornerSubPix(img, corners, Size(11, 11), Size(-1, -1),
TermCriteria(TermCriteria::COUNT + TermCriteria::EPS,
30, 0.01));
}
if (k == 2)
{
goodImageList.push_back(imagelist[i * 2]);
goodImageList.push_back(imagelist[i * 2 + 1]);
j++;
}
}
cout << j << " pairs have been successfully detected.\n";
nimages = j;
if (nimages < 2)
{
cout << "Error: too little pairs to run the calibration\n";
return false;
}
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
objectPoints.resize(nimages);
for (i = 0; i < nimages; i++)
{
for (j = 0; j < boardSize.height; j++)
for (k = 0; k < boardSize.width; k++)
objectPoints[i].push_back(Point3f(k*squareSize, j*squareSize, 0));
}
cout << "Running stereo calibration ...\n";
Mat cameraMatrix[2], distCoeffs[2];
cameraMatrix[0] = initCameraMatrix2D(objectPoints, imagePoints[0], imageSize, 0);
cameraMatrix[1] = initCameraMatrix2D(objectPoints, imagePoints[1], imageSize, 0);
Mat R, T, E, F;
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, E, F,
CALIB_FIX_ASPECT_RATIO +
CALIB_ZERO_TANGENT_DIST +
CALIB_USE_INTRINSIC_GUESS +
CALIB_SAME_FOCAL_LENGTH +
CALIB_RATIONAL_MODEL +
CALIB_FIX_K3 + CALIB_FIX_K4 + CALIB_FIX_K5,
TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, 1e-5));
cout << "done with RMS error=" << rms << endl;
// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
double err = 0;
int npoints = 0;
vector
for (i = 0; i < nimages; i++)
{
int npt = (int)imagePoints[0][i].size();
Mat imgpt[2];
for (k = 0; k < 2; k++)
{
imgpt[k] = Mat(imagePoints[k][i]);
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
computeCorrespondEpilines(imgpt[k], k + 1, F, lines[k]);
}
for (j = 0; j < npt; j++)
{
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
cout << "average epipolar err = " << err / npoints << endl;
// save intrinsic parameters
FileStorage fs(m_IntParamPath.toStdString(), FileStorage::WRITE);
if (fs.isOpened())
{
fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
"M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
fs.release();
}
else
cout << "Error: can not save the intrinsic parameters\n";
Mat R1, R2, P1, P2, Q;
Rect validRoi[2];
stereoRectify(cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, R1, R2, P1, P2, Q,
CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);
fs.open(m_ExtParamPath.toStdString(), FileStorage::WRITE);
if (fs.isOpened())
{
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
fs.release();
}
else
cout << "Error: can not save the extrinsic parameters\n";
// OpenCV can handle left-right
// or up-down camera arrangements
bool isVerticalStereo = fabs(P2.at
Mat rmap[2][2];
// IF BY CALIBRATED (BOUGUET'S METHOD)
if (useCalibrated)
{
// we already computed everything
}
// OR ELSE HARTLEY'S METHOD
else
// use intrinsic parameters of each camera, but
// compute the rectification transformation directly
// from the fundamental matrix
{
vector
for (k = 0; k < 2; k++)
{
for (i = 0; i < nimages; i++)
std::copy(imagePoints[k][i].begin(), imagePoints[k][i].end(), back_inserter(allimgpt[k]));
}
F = findFundamentalMat(Mat(allimgpt[0]), Mat(allimgpt[1]), FM_8POINT, 0, 0);
Mat H1, H2;
stereoRectifyUncalibrated(Mat(allimgpt[0]), Mat(allimgpt[1]), F, imageSize, H1, H2, 3);
R1 = cameraMatrix[0].inv()*H1*cameraMatrix[0];
R2 = cameraMatrix[1].inv()*H2*cameraMatrix[1];
P1 = cameraMatrix[0];
P2 = cameraMatrix[1];
}
fs.open(m_ExtParamPath.toStdString(), FileStorage::WRITE);
if (fs.isOpened())
{
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
fs.release();
}
else
cout << "Error: can not save the extrinsic parameters\n";
//Precompute maps for cv::remap()
initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1, imageSize, CV_16SC2, rmap[0][0], rmap[0][1]);
initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2, imageSize, CV_16SC2, rmap[1][0], rmap[1][1]);
Mat canvas;
double sf;
int w, h;
if (!isVerticalStereo)
{
sf = 600. / MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h, w * 2, CV_8UC3);
}
else
{
sf = 300. / MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h * 2, w, CV_8UC3);
}
for (i = 0; i < nimages; i++)
{
for (k = 0; k < 2; k++)
{
Mat img = imread(goodImageList[i * 2 + k], 0), rimg, cimg;
remap(img, rimg, rmap[k][0], rmap[k][1], INTER_LINEAR);
cvtColor(rimg, cimg, COLOR_GRAY2BGR);
Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
cv::resize(cimg, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);
if (useCalibrated)
{
Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),
cvRound(validRoi[k].width*sf), cvRound(validRoi[k].height*sf));
rectangle(canvasPart, vroi, Scalar(0, 0, 255), 3, 8);
}
}
if (!isVerticalStereo)
for (j = 0; j < canvas.rows; j += 16)
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
else
for (j = 0; j < canvas.cols; j += 16)
line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
imshow("rectified", canvas);
char c = (char)waitKey();
if (c == 27 || c == 'q' || c == 'Q')
break;
}
return true;
}
图片文件xml如下
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/left_1.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/right_1.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/left_2.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/right_2.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/left_3.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/right_3.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/left_4.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/right_4.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/left_5.bmp"
"D:/Code/vision/Binocular_Demo/Binocular_Calibration/Image/right_5.bmp"