Camera calibration with square chessboard {#tutorial_camera_calibration_square_chess}
=========================================

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 code that detects a chessboard in an image and finds its distance from the
camera. You can apply this method to any object with known 3D geometry; which you 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 a 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 would you calculate distance from the camera origin to any one of the corners?
Answer: As our image lies in a 3D space, firstly we would calculate the relative camera pose. This would give us 3D to 2D correspondences. Next, we can apply a simple L2 norm to calculate distance between any point (end point for corners).
