####### Calib3D ####### .. highlight:: cpp Camera calibration ================== 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], 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`` 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 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?