本文介绍了OpenCV StereoSGBM提供了非常差的视差图的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
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;
}
这是我使用不同参数的视差图代码:
And this is my disparity map code with different params:
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?
I'm new in OpenCV and image processing, what I'm doing wrong?
推荐答案
尝试使用此校准文件- https://github.com/foxymop/3DPoseEstimation/blob/master/src/out_camera_data.yml 我也试图校准相机，但是要得到很小的误差确实很困难，并且与尝试查找相机的参数相比，使用此配置给我带来了更好的结果(很可能我的相机与校准文件中的相机相似).最终，您可能会尝试完全不使用校准文件.
Try to use this calibration file - https://github.com/foxymop/3DPoseEstimation/blob/master/src/out_camera_data.yml I was trying to calibrate my camera as well, but getting small error is really hard and using this configurations gave me better results than trying to find parameters of my camera (most likely my camera is similar to the one from calibration file). Eventually you may try to not use calibration file at all.
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