Merge pull request #25028 from asmorkalov:as/fisheye_solvepnp

solvePnP implementation for Fisheye camera model #25028

Credits to Linfei Pan
Extracted from https://github.com/opencv/opencv/pull/24052

**Warning:** The patch changes Obj-C generator behaviour and adds "fisheye_" prefix for all ObjC functions from namespace.

### 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>
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>

modules/calib3d/include/opencv2/calib3d.hpp

@@ -4055,6 +4055,45 @@ optimization. It is the \f$max(width,height)/\pi\f$ or the provided \f$f_x\f$, \
                                   OutputArray R, OutputArray T, int flags = fisheye::CALIB_FIX_INTRINSIC,
                                   TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
 
+    /**
+    @brief Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.
+
+    @param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or
+    1xN/Nx1 3-channel, where N is the number of points. vector\<Point3d\> can be also passed here.
+    @param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+    where N is the number of points. vector\<Point2d\> can be also passed here.
+    @param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+    @param distCoeffs Input vector of distortion coefficients (4x1/1x4).
+    @param rvec Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+    the model coordinate system to the camera coordinate system.
+    @param tvec Output translation vector.
+    @param useExtrinsicGuess Parameter used for #SOLVEPNP_ITERATIVE. If true (1), the function uses
+    the provided rvec and tvec values as initial approximations of the rotation and translation
+    vectors, respectively, and further optimizes them.
+    @param flags Method for solving a PnP problem: see @ref calib3d_solvePnP_flags
+    This function returns the rotation and the translation vectors that transform a 3D point expressed in the object
+    coordinate frame to the camera coordinate frame, using different methods:
+    - P3P methods (@ref SOLVEPNP_P3P, @ref SOLVEPNP_AP3P): need 4 input points to return a unique solution.
+    - @ref SOLVEPNP_IPPE Input points must be >= 4 and object points must be coplanar.
+    - @ref SOLVEPNP_IPPE_SQUARE Special case suitable for marker pose estimation.
+    Number of input points must be 4. Object points must be defined in the following order:
+    - point 0: [-squareLength / 2,  squareLength / 2, 0]
+    - point 1: [ squareLength / 2,  squareLength / 2, 0]
+    - point 2: [ squareLength / 2, -squareLength / 2, 0]
+    - point 3: [-squareLength / 2, -squareLength / 2, 0]
+    - for all the other flags, number of input points must be >= 4 and object points can be in any configuration.
+    @param criteria Termination criteria for internal undistortPoints call.
+    The function interally undistorts points with @ref undistortPoints and call @ref cv::solvePnP,
+    thus the input are very similar. Check there and Perspective-n-Points is described in @ref calib3d_solvePnP
+    for more information.
+    */
+    CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
+                                InputArray cameraMatrix, InputArray distCoeffs,
+                                OutputArray rvec, OutputArray tvec,
+                                bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE,
+                                TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 10, 1e-8)
+                              );
+
 //! @} calib3d_fisheye
 } // end namespace fisheye
 

modules/calib3d/misc/objc/gen_dict.json

@@ -1,4 +1,7 @@
 {
+    "namespaces_dict": {
+        "cv.fisheye": "fisheye"
+    },
     "func_arg_fix" : {
         "Calib3d" : {
             "findCirclesGrid" : { "blobDetector" : {"defval" : "cv::SimpleBlobDetector::create()"} }

modules/calib3d/src/fisheye.cpp

@@ -1148,6 +1148,20 @@ double cv::fisheye::stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayO
     return rms;
 }
 
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////
+/// cv::fisheye::solvePnP
+
+bool cv::fisheye::solvePnP( InputArray opoints, InputArray ipoints,
+               InputArray cameraMatrix, InputArray distCoeffs,
+               OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess,
+               int flags, TermCriteria criteria)
+{
+
+    Mat imagePointsNormalized;
+    cv::fisheye::undistortPoints(ipoints, imagePointsNormalized, cameraMatrix, distCoeffs, noArray(), cameraMatrix, criteria);
+    return cv::solvePnP(opoints, imagePointsNormalized, cameraMatrix, noArray(), rvec, tvec, useExtrinsicGuess, flags);
+}
+
 namespace cv{ namespace {
 void subMatrix(const Mat& src, Mat& dst, const std::vector<uchar>& cols, const std::vector<uchar>& rows)
 {

modules/calib3d/test/test_fisheye.cpp

@@ -150,6 +150,28 @@ TEST_F(fisheyeTest, distortUndistortPoints)
     }
 }
 
+TEST_F(fisheyeTest, solvePnP)
+{
+    const int n = 16;
+
+    cv::Mat obj_points(1, n, CV_64FC3);
+    theRNG().fill(obj_points, cv::RNG::NORMAL, 2, 1);
+    obj_points = cv::abs(obj_points) * 10;
+
+    cv::Mat rvec;
+    cv::Rodrigues(this->R, rvec);
+    cv::Mat img_points;
+    cv::fisheye::projectPoints(obj_points, img_points, rvec, this->T, this->K, this->D);
+
+    cv::Mat rvec_pred;
+    cv::Mat tvec_pred;
+    bool converged = cv::fisheye::solvePnP(obj_points, img_points, this->K, this->D, rvec_pred, tvec_pred);
+    EXPECT_MAT_NEAR(rvec, rvec_pred, 1e-6);
+    EXPECT_MAT_NEAR(this->T, tvec_pred, 1e-6);
+
+    ASSERT_TRUE(converged);
+}
+
 TEST_F(fisheyeTest, undistortImage)
 {
     // we use it to reduce patch size for images in testdata