Point Cloud Library (PCL)
1.9.1
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38 #ifndef PCL_SEGMENT_DIFFERENCES_H_
39 #define PCL_SEGMENT_DIFFERENCES_H_
41 #include <pcl/pcl_base.h>
42 #include <pcl/search/pcl_search.h>
55 template <
typename Po
intT>
62 template <
typename Po
intT>
63 PCL_DEPRECATED(
"getPointCloudDifference() does not use the tgt parameter, thus it is deprecated and will be removed in future releases.")
71 getPointCloudDifference<PointT> (src, threshold, tree, output);
83 template <
typename Po
intT>
113 inline PointCloudConstPtr
const
170 #ifdef PCL_NO_PRECOMPILE
171 #include <pcl/segmentation/impl/segment_differences.hpp>
174 #endif //#ifndef PCL_SEGMENT_DIFFERENCES_H_
This file defines compatibility wrappers for low level I/O functions.
void getPointCloudDifference(const pcl::PointCloud< PointT > &src, double threshold, const boost::shared_ptr< pcl::search::Search< PointT > > &tree, pcl::PointCloud< PointT > &output)
Obtain the difference between two aligned point clouds as another point cloud, given a distance thres...
boost::shared_ptr< PointCloud< PointT > > Ptr
PointCloud::Ptr PointCloudPtr
PointCloudConstPtr input_
The input point cloud dataset.
PointCloud::ConstPtr PointCloudConstPtr
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
void segment(PointCloud &output)
Segment differences between two input point clouds.
PointCloud represents the base class in PCL for storing collections of 3D points.
A point structure representing Euclidean xyz coordinates, and the RGB color.
void setDistanceThreshold(double sqr_threshold)
Set the maximum distance tolerance (squared) between corresponding points in the two input datasets.
boost::shared_ptr< ::pcl::PointIndices > Ptr
KdTreePtr tree_
A pointer to the spatial search object.
PointCloudConstPtr target_
The input target point cloud dataset.
pcl::search::Search< PointT >::Ptr KdTreePtr
pcl::PointCloud< PointT > PointCloud
PointIndices::ConstPtr PointIndicesConstPtr
SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the ...
void setTargetCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the target dataset against which we compare the input cloud given in setInputClo...
const PointCloudConstPtr getTargetCloud()
Get a pointer to the input target point cloud dataset.
double distance_threshold_
The distance tolerance (squared) as a measure in the L2 Euclidean space between corresponding points.
PointCloud::ConstPtr PointCloudConstPtr
SegmentDifferences()
Empty constructor.
virtual std::string getClassName() const
Class getName method.
pcl::search::Search< PointT > KdTree
double getDistanceThreshold()
Get the squared distance tolerance between corresponding points as a measure in the L2 Euclidean spac...
boost::shared_ptr< ::pcl::PointIndices const > ConstPtr
bool deinitCompute()
This method should get called after finishing the actual computation.
IndicesPtr indices_
A pointer to the vector of point indices to use.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
PointIndices::Ptr PointIndicesPtr
KdTreePtr getSearchMethod()
Get a pointer to the search method used.
bool initCompute()
This method should get called before starting the actual computation.
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.