Point Cloud Library (PCL)  1.7.0
/tmp/buildd/pcl-1.7-1.7.0/sample_consensus/include/pcl/sample_consensus/sac_model_normal_plane.h
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00040 
00041 #ifndef PCL_SAMPLE_CONSENSUS_MODEL_NORMALPLANE_H_
00042 #define PCL_SAMPLE_CONSENSUS_MODEL_NORMALPLANE_H_
00043 
00044 #include <pcl/sample_consensus/sac_model.h>
00045 #include <pcl/sample_consensus/sac_model_plane.h>
00046 #include <pcl/sample_consensus/sac_model_perpendicular_plane.h>
00047 #include <pcl/sample_consensus/model_types.h>
00048 
00049 namespace pcl
00050 {
00051   /** \brief SampleConsensusModelNormalPlane defines a model for 3D plane
00052     * segmentation using additional surface normal constraints. Basically this
00053     * means that checking for inliers will not only involve a "distance to
00054     * model" criterion, but also an additional "maximum angular deviation"
00055     * between the plane's normal and the inlier points normals.
00056     *
00057     * The model coefficients are defined as:
00058     *   - \b a : the X coordinate of the plane's normal (normalized)
00059     *   - \b b : the Y coordinate of the plane's normal (normalized)
00060     *   - \b c : the Z coordinate of the plane's normal (normalized)
00061     *   - \b d : the fourth <a href="http://mathworld.wolfram.com/HessianNormalForm.html">Hessian component</a> of the plane's equation
00062     *
00063     * To set the influence of the surface normals in the inlier estimation
00064     * process, set the normal weight (0.0-1.0), e.g.:
00065     * \code
00066     * SampleConsensusModelNormalPlane<pcl::PointXYZ, pcl::Normal> sac_model;
00067     * ...
00068     * sac_model.setNormalDistanceWeight (0.1);
00069     * ...
00070     * \endcode
00071     *
00072     * \author Radu B. Rusu and Jared Glover
00073     * \ingroup sample_consensus
00074     */
00075   template <typename PointT, typename PointNT>
00076   class SampleConsensusModelNormalPlane : public SampleConsensusModelPlane<PointT>, public SampleConsensusModelFromNormals<PointT, PointNT>
00077   {
00078     public:
00079       using SampleConsensusModel<PointT>::input_;
00080       using SampleConsensusModel<PointT>::indices_;
00081       using SampleConsensusModelFromNormals<PointT, PointNT>::normals_;
00082       using SampleConsensusModelFromNormals<PointT, PointNT>::normal_distance_weight_;
00083       using SampleConsensusModel<PointT>::error_sqr_dists_;
00084       using SampleConsensusModelPlane<PointT>::isModelValid;
00085 
00086       typedef typename SampleConsensusModel<PointT>::PointCloud PointCloud;
00087       typedef typename SampleConsensusModel<PointT>::PointCloudPtr PointCloudPtr;
00088       typedef typename SampleConsensusModel<PointT>::PointCloudConstPtr PointCloudConstPtr;
00089 
00090       typedef typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNPtr PointCloudNPtr;
00091       typedef typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNConstPtr PointCloudNConstPtr;
00092 
00093       typedef boost::shared_ptr<SampleConsensusModelNormalPlane> Ptr;
00094 
00095       /** \brief Constructor for base SampleConsensusModelNormalPlane.
00096         * \param[in] cloud the input point cloud dataset
00097         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
00098         */
00099       SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, 
00100                                        bool random = false) 
00101         : SampleConsensusModelPlane<PointT> (cloud, random)
00102         , SampleConsensusModelFromNormals<PointT, PointNT> ()
00103       {
00104       }
00105 
00106       /** \brief Constructor for base SampleConsensusModelNormalPlane.
00107         * \param[in] cloud the input point cloud dataset
00108         * \param[in] indices a vector of point indices to be used from \a cloud
00109         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
00110         */
00111       SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, 
00112                                        const std::vector<int> &indices,
00113                                        bool random = false) 
00114         : SampleConsensusModelPlane<PointT> (cloud, indices, random)
00115         , SampleConsensusModelFromNormals<PointT, PointNT> ()
00116       {
00117       }
00118       
00119       /** \brief Empty destructor */
00120       virtual ~SampleConsensusModelNormalPlane () {}
00121 
00122       /** \brief Select all the points which respect the given model coefficients as inliers.
00123         * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
00124         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
00125         * \param[out] inliers the resultant model inliers
00126         */
00127       void 
00128       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
00129                             const double threshold, 
00130                             std::vector<int> &inliers);
00131 
00132       /** \brief Count all the points which respect the given model coefficients as inliers. 
00133         * 
00134         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
00135         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
00136         * \return the resultant number of inliers
00137         */
00138       virtual int
00139       countWithinDistance (const Eigen::VectorXf &model_coefficients, 
00140                            const double threshold);
00141 
00142       /** \brief Compute all distances from the cloud data to a given plane model.
00143         * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
00144         * \param[out] distances the resultant estimated distances
00145         */
00146       void 
00147       getDistancesToModel (const Eigen::VectorXf &model_coefficients, 
00148                            std::vector<double> &distances);
00149 
00150       /** \brief Return an unique id for this model (SACMODEL_NORMAL_PLANE). */
00151       inline pcl::SacModel 
00152       getModelType () const { return (SACMODEL_NORMAL_PLANE); }
00153 
00154       EIGEN_MAKE_ALIGNED_OPERATOR_NEW
00155   };
00156 }
00157 
00158 #ifdef PCL_NO_PRECOMPILE
00159 #include <pcl/sample_consensus/impl/sac_model_normal_plane.hpp>
00160 #endif
00161 
00162 #endif  //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_NORMALPLANE_H_