The goal of this tutorial is to learn how to calibrate a camera given a set of chessboard images.
Test data: use images in your data/chess folder.
- Compile opencv with samples by setting BUILD_EXAMPLES to ON in cmake configuration.
- Go to bin folder and use imagelist_creator to create an XML/YAML list of your images.
- Then, run calibration sample to get camera parameters. Use square size equal to 3cm.
Pose estimation
Now, let us write a code that detects a chessboard in a new image and finds its distance from the camera. You can apply the same method to any object with known 3D geometry that you can detect in an image.
Test data: use chess_test*.jpg images from your data folder.
-
Create an empty console project. Load a test image:
Mat img = imread(argv[1], IMREAD_GRAYSCALE); -
Detect a chessboard in this image using findChessboard function.
bool found = findChessboardCorners( img, boardSize, ptvec, CALIB_CB_ADAPTIVE_THRESH ); -
Now, write a function that generates a vector<Point3f> array of 3d coordinates of a chessboard in any coordinate system. For simplicity, let us choose a system such that one of the chessboard corners is in the origin and the board is in the plane z = 0.
-
Read camera parameters from XML/YAML file:
FileStorage fs(filename, FileStorage::READ); Mat intrinsics, distortion; fs["camera_matrix"] >> intrinsics; fs["distortion_coefficients"] >> distortion; -
Now we are ready to find chessboard pose by running solvePnP:
vector<Point3f> boardPoints; // fill the array ... solvePnP(Mat(boardPoints), Mat(foundBoardCorners), cameraMatrix, distCoeffs, rvec, tvec, false); -
Calculate reprojection error like it is done in calibration sample (see opencv/samples/cpp/calibration.cpp, function computeReprojectionErrors).
Question: how to calculate the distance from the camera origin to any of the corners?
本教程详细介绍了如何使用棋盘格图像集进行相机校准,包括编译OpenCV示例、创建图像列表、运行校准样本获取相机参数等步骤。此外,还讲解了如何检测新图像中的棋盘格并估算其与相机的距离,适用于任何已知3D几何的对象检测。
1万+

被折叠的 条评论
为什么被折叠?



