From: edgarriba Date: Fri, 25 Jul 2014 09:39:06 +0000 (+0200) Subject: Update documentation for DLS X-Git-Tag: accepted/tizen/6.0/unified/20201030.111113~3003^2~95 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=5f54a22d2945dd8998d11d027e1f31e0e4b36f02;p=platform%2Fupstream%2Fopencv.git Update documentation for DLS --- diff --git a/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst b/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst index 14d7c8d..5cd1996 100644 --- a/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst +++ b/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst @@ -585,6 +585,7 @@ Finds an object pose from 3D-2D point correspondences. * **CV_ITERATIVE** Iterative method is based on Levenberg-Marquardt optimization. In this case the function finds such a pose that minimizes reprojection error, that is the sum of squared distances between the observed projections ``imagePoints`` and the projected (using :ocv:func:`projectPoints` ) ``objectPoints`` . * **CV_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. * **CV_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". + * **CV_DLS** Method is based on the paper of Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP". 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.