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.
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, CV_LOAD_IMAGE_GRAYSCALE);
Detect a chessboard in this image using findChessboard function.
bool found = findChessboardCorners( img, boardSize, ptvec, CV_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?