Point Cloud Library (PCL)  1.7.0
/tmp/buildd/pcl-1.7-1.7.0/segmentation/include/pcl/segmentation/segment_differences.h
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00037 
00038 #ifndef PCL_SEGMENT_DIFFERENCES_H_
00039 #define PCL_SEGMENT_DIFFERENCES_H_
00040 
00041 #include <pcl/pcl_base.h>
00042 #include <pcl/search/pcl_search.h>
00043 
00044 namespace pcl
00045 {
00046   ////////////////////////////////////////////////////////////////////////////////////////////
00047   /** \brief Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold.
00048     * \param src the input point cloud source
00049     * \param tgt the input point cloud target we need to obtain the difference against
00050     * \param threshold the distance threshold (tolerance) for point correspondences. (e.g., check if f a point p1 from 
00051     * src has a correspondence > threshold than a point p2 from tgt)
00052     * \param tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching built over \a tgt
00053     * \param output the resultant output point cloud difference
00054     * \ingroup segmentation
00055     */
00056   template <typename PointT> 
00057   void getPointCloudDifference (
00058       const pcl::PointCloud<PointT> &src, const pcl::PointCloud<PointT> &tgt, 
00059       double threshold, const boost::shared_ptr<pcl::search::Search<PointT> > &tree,
00060       pcl::PointCloud<PointT> &output);
00061 
00062   ////////////////////////////////////////////////////////////////////////////////////////////
00063   ////////////////////////////////////////////////////////////////////////////////////////////
00064   ////////////////////////////////////////////////////////////////////////////////////////////
00065   /** \brief @b SegmentDifferences obtains the difference between two spatially
00066     * aligned point clouds and returns the difference between them for a maximum
00067     * given distance threshold.
00068     * \author Radu Bogdan Rusu
00069     * \ingroup segmentation
00070     */
00071   template <typename PointT>
00072   class SegmentDifferences: public PCLBase<PointT>
00073   {
00074     typedef PCLBase<PointT> BasePCLBase;
00075 
00076     public:
00077       typedef pcl::PointCloud<PointT> PointCloud;
00078       typedef typename PointCloud::Ptr PointCloudPtr;
00079       typedef typename PointCloud::ConstPtr PointCloudConstPtr;
00080 
00081       typedef typename pcl::search::Search<PointT> KdTree;
00082       typedef typename pcl::search::Search<PointT>::Ptr KdTreePtr;
00083 
00084       typedef PointIndices::Ptr PointIndicesPtr;
00085       typedef PointIndices::ConstPtr PointIndicesConstPtr;
00086 
00087       /** \brief Empty constructor. */
00088       SegmentDifferences () : 
00089         tree_ (), target_ (), distance_threshold_ (0)
00090       {};
00091 
00092       /** \brief Provide a pointer to the target dataset against which we
00093         * compare the input cloud given in setInputCloud
00094         *
00095         * \param cloud the target PointCloud dataset
00096         */
00097       inline void 
00098       setTargetCloud (const PointCloudConstPtr &cloud) { target_ = cloud; }
00099 
00100       /** \brief Get a pointer to the input target point cloud dataset. */
00101       inline PointCloudConstPtr const 
00102       getTargetCloud () { return (target_); }
00103 
00104       /** \brief Provide a pointer to the search object.
00105         * \param tree a pointer to the spatial search object.
00106         */
00107       inline void 
00108       setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
00109 
00110       /** \brief Get a pointer to the search method used. */
00111       inline KdTreePtr 
00112       getSearchMethod () { return (tree_); }
00113 
00114       /** \brief Set the maximum distance tolerance (squared) between corresponding
00115         * points in the two input datasets.
00116         *
00117         * \param sqr_threshold the squared distance tolerance as a measure in L2 Euclidean space
00118         */
00119       inline void 
00120       setDistanceThreshold (double sqr_threshold) { distance_threshold_ = sqr_threshold; }
00121 
00122       /** \brief Get the squared distance tolerance between corresponding points as a
00123         * measure in the L2 Euclidean space.
00124         */
00125       inline double 
00126       getDistanceThreshold () { return (distance_threshold_); }
00127 
00128       /** \brief Segment differences between two input point clouds.
00129         * \param output the resultant difference between the two point clouds as a PointCloud
00130         */
00131       void 
00132       segment (PointCloud &output);
00133 
00134     protected:
00135       // Members derived from the base class
00136       using BasePCLBase::input_;
00137       using BasePCLBase::indices_;
00138       using BasePCLBase::initCompute;
00139       using BasePCLBase::deinitCompute;
00140 
00141       /** \brief A pointer to the spatial search object. */
00142       KdTreePtr tree_;
00143 
00144       /** \brief The input target point cloud dataset. */
00145       PointCloudConstPtr target_;
00146 
00147       /** \brief The distance tolerance (squared) as a measure in the L2
00148         * Euclidean space between corresponding points. 
00149         */
00150       double distance_threshold_;
00151 
00152       /** \brief Class getName method. */
00153       virtual std::string 
00154       getClassName () const { return ("SegmentDifferences"); }
00155   };
00156 }
00157 
00158 #ifdef PCL_NO_PRECOMPILE
00159 #include <pcl/segmentation/impl/segment_differences.hpp>
00160 #endif
00161 
00162 #endif  //#ifndef PCL_SEGMENT_DIFFERENCES_H_