opencv/doc/tutorials/calib3d.rst

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Calib3D
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.. 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.
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Compile opencv with samples by setting ``BUILD_EXAMPLES`` to ``ON`` in cmake configuration.
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Go to ``bin`` folder and use ``imagelist_creator`` to create an ``XML/YAML`` list of your images.
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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.
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Create an empty console project. Load a test image: ::
Mat img = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
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Detect a chessboard in this image using findChessboard function. ::
bool found = findChessboardCorners( img, boardSize, ptvec, CV_CALIB_CB_ADAPTIVE_THRESH );
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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*.
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Read camera parameters from XML/YAML file: ::
FileStorage fs(filename, FileStorage::READ);
Mat intrinsics, distortion;
fs["camera_matrix"] >> intrinsics;
fs["distortion_coefficients"] >> distortion;
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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);
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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?