这些是我的校准代码：
void calibrate()
{
int numBoards = 10;
int board_w = 6;
int board_h = 9;
Size board_sz = Size(board_w, board_h);
int board_n = board_w*board_h;
vector<vector<Point3f> > object_points;
vector<vector<Point2f> > imagePoints1, imagePoints2;
vector<Point2f> corners1, corners2;
vector<Point3f> obj;
for (int j=0; j<board_n; j++)
{
obj.push_back(Point3f(j/board_w, j%board_w, 0.0f));
}
Mat img1, img2, gray1, gray2;
VideoCapture cap1(0);
VideoCapture cap2(1);
int success = 0, k = 0;
bool found1 = false, found2 = false;
namedWindow("left 1");
namedWindow("right 1");
while (success < numBoards)
{
cap1 >> img1;
cap2 >> img2;
cvtColor(img1, gray1, CV_BGR2GRAY);
cvtColor(img2, gray2, CV_BGR2GRAY);
found1 = findChessboardCorners(img1, board_sz, corners1, CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FILTER_QUADS);
found2 = findChessboardCorners(img2, board_sz, corners2, CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FILTER_QUADS);
if (found1)
{
cornerSubPix(gray1, corners1, Size(11, 11), Size(-1, -1), TermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 30, 0.1));
drawChessboardCorners(gray1, board_sz, corners1, found1);
}
if (found2)
{
cornerSubPix(gray2, corners2, Size(11, 11), Size(-1, -1), TermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 30, 0.1));
drawChessboardCorners(gray2, board_sz, corners2, found2);
}
imshow("left 1", img1);
imshow("right 1", img2);
k = cv::waitKey(2);
if(found1) cout<<"found 1"<<endl;
if(found2) cout<<"found 2"<<endl;
if(!found1 && !found2) cout<<"no"<<endl;
if ( found1 && found2)
{
imagePoints1.push_back(corners1);
imagePoints2.push_back(corners2);
object_points.push_back(obj);
printf ("Corners stored\n");
success++;
if (success >= numBoards)
{
break;
}
}
}
destroyAllWindows();
printf("Starting Calibration\n");
Mat CM1 = Mat(3, 3, CV_64FC1);
Mat CM2 = Mat(3, 3, CV_64FC1);
Mat D1, D2;
Mat R, T, E, F;
stereoCalibrate(object_points, imagePoints1, imagePoints2,
CM1, D1, CM2, D2, img1.size(), R, T, E, F,
cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_SAME_FOCAL_LENGTH | CV_CALIB_ZERO_TANGENT_DIST);
FileStorage fs1("mystereocalib.yml", FileStorage::WRITE);
fs1 << "CM1" << CM1;
fs1 << "CM2" << CM2;
fs1 << "D1" << D1;
fs1 << "D2" << D2;
fs1 << "R" << R;
fs1 << "T" << T;
fs1 << "E" << E;
fs1 << "F" << F;
printf("Done Calibration\n");
printf("Starting Rectification\n");
Mat R1, R2, P1, P2, Q;
stereoRectify(CM1, D1, CM2, D2, img1.size(), R, T, R1, R2, P1, P2, Q);
fs1 << "R1" << R1;
fs1 << "R2" << R2;
fs1 << "P1" << P1;
fs1 << "P2" << P2;
fs1 << "Q" << Q;
printf("Done Rectification\n");
printf("Applying Undistort\n");
Mat map1x, map1y, map2x, map2y;
Mat imgU1, imgU2;
initUndistortRectifyMap(CM1, D1, R1, P1, img1.size(), CV_32FC1, map1x, map1y);
initUndistortRectifyMap(CM2, D2, R2, P2, img2.size(), CV_32FC1, map2x, map2y);
printf("Undistort complete\n");
cap1.release();
cap2.release();
return;
}
这是我的差异地图代码，有不同的参数：
int main(int argc, char* argv[])
{
//calibrate();
Mat img1, img2;
VideoCapture cap1 = VideoCapture(0);
VideoCapture cap2 = VideoCapture(1);
cap1 >> img1;
cap2 >> img2;
Mat Q;
FileStorage fs("mystereocalib.yml", FileStorage::READ);
fs["Q"] >> Q;
Mat CM1, CM2, D1, D2, P1, P2, R1, R2;
fs["CM1"] >> CM1;
fs["CM2"] >> CM2;
fs["D1"] >> D1;
fs["D2"] >> D2;
fs["P1"] >> P1;
fs["P2"] >> P2;
fs["R1"] >> R1;
fs["R2"] >> R2;
fs.release();
Mat map1x, map1y, map2x, map2y;
Mat imgU1, imgU2;
initUndistortRectifyMap(CM1, D1, R1, P1, img1.size(), CV_32FC1, map1x, map1y);
initUndistortRectifyMap(CM2, D2, R2, P2, img2.size(), CV_32FC1, map2x, map2y);
while(1)
{
cap1 >> img1;
cap2 >> img2;
imshow("img1", img1);
imshow("img2", img2);
cv::waitKey(1);
remap(img1, imgU1, map1x, map1y, INTER_LINEAR, BORDER_CONSTANT, Scalar());
remap(img2, imgU2, map2x, map2y, INTER_LINEAR, BORDER_CONSTANT, Scalar());
Mat g1,g2, disp, disp8;
cvtColor(imgU1, g1, CV_BGR2GRAY);
cvtColor(imgU2, g2, CV_BGR2GRAY);
/*StereoSGBM sbm;
sbm.SADWindowSize = 5;
sbm.numberOfDisparities = 144;
sbm.preFilterCap = 63;
sbm.minDisparity = -39;
sbm.uniquenessRatio = 10;
sbm.speckleWindowSize = 100;
sbm.speckleRange = 32;
sbm.disp12MaxDiff = 2;
sbm.fullDP = true;
sbm.P1 = 216;
sbm.P2 = 864;
sbm(g1, g2, disp);*/
int sadSize = 3;
StereoSGBM sbm;
sbm.SADWindowSize = sadSize;
sbm.numberOfDisparities = 128;//144;
sbm.preFilterCap = 63;
sbm.minDisparity = 0; //-39;
sbm.uniquenessRatio = 10;
sbm.speckleWindowSize = 100;
sbm.speckleRange = 32;
sbm.disp12MaxDiff = 1;
sbm.fullDP = true;
sbm.P1 = sadSize*sadSize*4;
sbm.P2 = sadSize*sadSize*32;
sbm(g1, g2, disp);
//StereoSGBM sgbm;
//sgbm.SADWindowSize = 5;
//sgbm.numberOfDisparities = 192;
//sgbm.preFilterCap = 4;
//sgbm.minDisparity = -64;
//sgbm.uniquenessRatio = 1;
//sgbm.speckleWindowSize = 150;
//sgbm.speckleRange = 2;
//sgbm.disp12MaxDiff = 10;
//sgbm.fullDP = false;
//sgbm.P1 = 600;
//sgbm.P2 = 2400;
//sgbm(g1, g2, disp);
//StereoBM sbm;
//sbm.state->SADWindowSize = 9;
//sbm.state->numberOfDisparities = 112;
//sbm.state->preFilterSize = 5;
//sbm.state->preFilterCap = 61;
//sbm.state->minDisparity = -39;
//sbm.state->textureThreshold = 507;
//sbm.state->uniquenessRatio = 0;
//sbm.state->speckleWindowSize = 0;
//sbm.state->speckleRange = 8;
//sbm.state->disp12MaxDiff = 1;
//sbm(g1, g2, disp);
normalize(disp, disp8, 0, 255, CV_MINMAX, CV_8U);
//disp.convertTo(disp8, CV_8U);
imshow("disp8", disp8);
}
waitKey(0);
return 0;
}
我是OpenCV和图像处理的新手，我做错了什么？
答案 0 :(得分：-1)
尝试使用此校准文件 - https://github.com/foxymop/3DPoseEstimation/blob/master/src/out_camera_data.yml我也尝试校准我的相机，但是获得小错误确实很难，并且使用此配置给我的结果比尝试查找相机的参数更好（大多数可能我的相机与校准文件中的相机相似）。最终你可能会尝试不使用校准文件。