Updating documentation

modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst

@@ -588,7 +588,7 @@ Finds an object pose from 3D-2D point correspondences.
             *  **SOLVEPNP_P3P**  Method is based on the paper of X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang "Complete Solution Classification for the Perspective-Three-Point Problem". In this case the function requires exactly four object and image points.
             *  **SOLVEPNP_EPNP** Method has been introduced by F.Moreno-Noguer, V.Lepetit and P.Fua in the paper "EPnP: Efficient Perspective-n-Point Camera Pose Estimation".
             *  **SOLVEPNP_DLS**  Method is based on the paper of Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP".
-            *  **SOLVEPNP_UPNP** Method is based on the paper of A.Penate-Sanchez, J.Andrade-Cetto, F.Moreno-Noguer. "Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation". In this case the function estimates the parameters :math:`f_x` and :math:`f_y` assuming that both have the same value. The ``cameraMatrix`` is updated with the estimated focal length.
+            *  **SOLVEPNP_UPNP** Method is based on the paper of A.Penate-Sanchez, J.Andrade-Cetto, F.Moreno-Noguer. "Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation". In this case the function also estimates the parameters :math:`f_x` and :math:`f_y` assuming that both have the same value. Then the ``cameraMatrix`` is updated with the estimated focal length.
 
 The function estimates the object pose given a set of object points, their corresponding image projections, as well as the camera matrix and the distortion coefficients.