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Merge pull request #25061 from asmorkalov:as/register_cameras
RegisterCameras function for heterogenious cameras pair #25061 Credits to Linfei Pan Extracted from https://github.com/opencv/opencv/pull/24052 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake --------- Co-authored-by: lpanaf <linpan@student.ethz.ch>
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Alexander Smorkalov
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@@ -422,6 +422,11 @@ enum { CALIB_CB_SYMMETRIC_GRID = 1,
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#define CALIB_NINTRINSIC 18 //!< Maximal size of camera internal parameters (initrinsics) vector
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enum CameraModel {
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CALIB_MODEL_PINHOLE = 0, //!< Pinhole camera model
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CALIB_MODEL_FISHEYE = 1, //!< Fisheye camera model
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};
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enum { CALIB_USE_INTRINSIC_GUESS = 0x00001, //!< Use user provided intrinsics as initial point for optimization.
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CALIB_FIX_ASPECT_RATIO = 0x00002, //!< Use with CALIB_USE_INTRINSIC_GUESS. The ratio fx/fy stays the same as in the input cameraMatrix.
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CALIB_FIX_PRINCIPAL_POINT = 0x00004, //!< The principal point (cx, cy) stays the same as in the input camera matrix. Image center is used as principal point, if CALIB_USE_INTRINSIC_GUESS is not set.
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@@ -1136,6 +1141,97 @@ CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints,
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OutputArray perViewErrors, int flags = CALIB_FIX_INTRINSIC,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) );
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/** @brief Calibrates a camera pair set up. This function finds the extrinsic parameters between the two cameras.
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@param objectPoints1 Vector of vectors of the calibration pattern points for camera 1.
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A similar structure as objectPoints in @ref calibrateCamera and for each pattern view,
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both cameras do not need to see the same object points. objectPoints1.size(), imagePoints1.size()
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nees to be equal,as well as objectPoints1[i].size(), imagePoints1[i].size() need to be equal for each i.
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@param objectPoints2 Vector of vectors of the calibration pattern points for camera 2.
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A similar structure as objectPoints1. objectPoints2.size(), and imagePoints2.size() nees to be equal,
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as well as objectPoints2[i].size(), imagePoints2[i].size() need to be equal for each i.
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However, objectPoints1[i].size() and objectPoints2[i].size() are not required to be equal.
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@param imagePoints1 Vector of vectors of the projections of the calibration pattern points,
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observed by the first camera. The same structure as in @ref calibrateCamera.
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@param imagePoints2 Vector of vectors of the projections of the calibration pattern points,
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observed by the second camera. The same structure as in @ref calibrateCamera.
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@param cameraMatrix1 Input/output camera intrinsic matrix for the first camera, the same as in
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@ref calibrateCamera. Furthermore, for the stereo case, additional flags may be used, see below.
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@param distCoeffs1 Input/output vector of distortion coefficients, the same as in
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@ref calibrateCamera.
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@param cameraModel1 Flag reflecting the type of model for camera 1 (pinhole / fisheye):
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- @ref CALIB_MODEL_PINHOLE pinhole camera model
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- @ref CALIB_MODEL_FISHEYE fisheye camera model
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@param cameraMatrix2 Input/output second camera intrinsic matrix for the second camera.
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See description for cameraMatrix1.
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@param distCoeffs2 Input/output lens distortion coefficients for the second camera. See
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description for distCoeffs1.
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@param cameraModel2 Flag reflecting the type of model for camera 2 (pinhole / fisheye).
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See description for cameraModel1.
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@param R Output rotation matrix. Together with the translation vector T, this matrix brings
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points given in the first camera's coordinate system to points in the second camera's
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coordinate system. In more technical terms, the tuple of R and T performs a change of basis
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from the first camera's coordinate system to the second camera's coordinate system. Due to its
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duality, this tuple is equivalent to the position of the first camera with respect to the
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second camera coordinate system.
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@param T Output translation vector, see description above.
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@param E Output essential matrix.
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@param F Output fundamental matrix.
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@param rvecs Output vector of rotation vectors ( @ref Rodrigues ) estimated for each pattern view in the
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coordinate system of the first camera of the stereo pair (e.g. std::vector<cv::Mat>). More in detail, each
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i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter
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description) brings the calibration pattern from the object coordinate space (in which object points are
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specified) to the camera coordinate space of the first camera of the stereo pair. In more technical terms,
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the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space
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to the camera coordinate space of the first camera of the stereo pair.
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@param tvecs Output vector of translation vectors estimated for each pattern view, see parameter description
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of previous output parameter ( rvecs ).
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@param perViewErrors Output vector of the RMS re-projection error estimated for each pattern view.
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@param flags Different flags that may be zero or a combination of the following values:
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- @ref CALIB_USE_EXTRINSIC_GUESS R and T contain valid initial values that are optimized further.
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@param criteria Termination criteria for the iterative optimization algorithm.
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The function estimates the transformation between two cameras similar to stereo pair calibration.
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The principle follows closely to @ref stereoCalibrate. To understand the problem of estimating the
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relative pose between a camera pair, please refer to the description there. The difference for
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this function is that, camera intrinsics are not optimized and two cameras are not required
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to have overlapping fields of view as long as they are observing the same calibration target
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and the absolute positions of each object point are known.
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The above illustration shows an example where such a case may become relevant.
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Additionally, it supports a camera pair with the mixed model (pinhole / fisheye).
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Similarly to #calibrateCamera, the function minimizes the total re-projection error for all the
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points in all the available views from both cameras.
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@return the final value of the re-projection error.
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@sa calibrateCamera, stereoCalibrate
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*/
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CV_EXPORTS_AS(registerCamerasExtended) double registerCameras( InputArrayOfArrays objectPoints1,
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InputArrayOfArrays objectPoints2,
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InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
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InputArray cameraMatrix1, InputArray distCoeffs1,
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CameraModel cameraModel1,
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InputArray cameraMatrix2, InputArray distCoeffs2,
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CameraModel cameraModel2,
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InputOutputArray R, InputOutputArray T, OutputArray E, OutputArray F,
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OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
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OutputArray perViewErrors,
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int flags = 0,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, 1e-6) );
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/// @overload
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CV_EXPORTS_W double registerCameras( InputArrayOfArrays objectPoints1,
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InputArrayOfArrays objectPoints2,
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InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
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InputArray cameraMatrix1, InputArray distCoeffs1,
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CameraModel cameraModel1,
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InputArray cameraMatrix2, InputArray distCoeffs2,
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CameraModel cameraModel2,
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InputOutputArray R, InputOutputArray T, OutputArray E, OutputArray F,
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OutputArray perViewErrors,
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int flags = 0,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, 1e-6) );
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/** @brief Estimates intrinsics and extrinsics (camera pose) for multi-camera system a.k.a multiview calibraton.
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@param[in] objPoints Calibration pattern object points. Expected shape: NUM_FRAMES x NUM_POINTS x 3. Supported data type: CV_32F.
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