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37 
38 #pragma once
39 
40 #include <pcl/types.h>
41 #include <pcl/point_cloud.h> // for PointCloud
42 #include <Eigen/Core> // for Matrix, RowMajor, Matrix3f
43 
44 /**
45   * \file common/geometry.h
46   * Defines some geometrical functions and utility functions
47   * \ingroup common
48   */
49 
50 /*@{*/
51 namespace pcl
52 {
53   /** \brief Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with
54     *        K = [[fx, s, cx], [0, fy, cy], [0, 0, 1]]
55     *        R = rotation matrix and
56     *        t = translation vector
57     *
58     * \param[in] cloud input cloud. Must be organized and from a projective device. e.g. stereo or kinect, ...
59     * \param[out] projection_matrix output projection matrix
60     * \param[in] indices The indices to be used to determine the projection matrix
61     * \return the resudial error. A high residual indicates, that the point cloud was not from a projective device.
62     */
63   template<typename PointT> double
64   estimateProjectionMatrix (typename pcl::PointCloud<PointT>::ConstPtr cloud, Eigen::Matrix<float, 3, 4, Eigen::RowMajor>& projection_matrix, const Indices& indices = {});
65 
66   /** \brief Determines the camera matrix from the given projection matrix.
67     * \note This method does NOT use a RQ decomposition, but uses the fact that the left 3x3 matrix P' of P squared eliminates the rotational part.
68     *       P' = K * R -> P' * P'^T = K * R * R^T * K = K * K^T
69     * \param[in] projection_matrix
70     * \param[out] camera_matrix
71     */
72   PCL_EXPORTS void
73   getCameraMatrixFromProjectionMatrix (const Eigen::Matrix<float, 3, 4, Eigen::RowMajor>& projection_matrix, Eigen::Matrix3f& camera_matrix);
74 }
75 
76 #include <pcl/common/impl/projection_matrix.hpp>
77