40 #include <pcl/pcl_exports.h>
42 #include <pcl/point_cloud.h>
44 #include <pcl/features/integral_image_normal.h>
45 #include <pcl/segmentation/organized_multi_plane_segmentation.h>
46 #include <pcl/common/transforms.h>
47 #include <pcl/gpu/people/label_common.h>
61 using Ptr = shared_ptr<OrganizedPlaneDetector>;
62 using ConstPtr = shared_ptr<const OrganizedPlaneDetector>;
167 void allocate_buffers(
int rows = 480,
int cols = 640);
Surface normal estimation on organized data using integral images.
OrganizedMultiPlaneSegmentation finds all planes present in the input cloud, and outputs a vector of ...
shared_ptr< const PointCloud< PointT > > ConstPtr
double mps_AngularThreshold_
void setMpsDistanceThreshold(double mpsDistanceThreshold)
void setNeMaxDepthChangeFactor(float neMaxDepthChangeFactor)
float ne_NormalSmoothingSize_
shared_ptr< const OrganizedPlaneDetector > ConstPtr
void emptyHostLabelProbability(HostLabelProbability &histogram)
pcl::device::LabelProbability P_l_dev_prev_
pcl::device::LabelProbability P_l_dev_
double mps_DistanceThreshold_
float getNeMaxDepthChangeFactor() const
double getMpsAngularThreshold() const
void setMpsMinInliers(int mpsMinInliers)
float ne_MaxDepthChangeFactor_
void setNeNormalSmoothingSize(float neNormalSmoothingSize)
int getMpsMinInliers() const
int copyAndClearHostLabelProbability(HostLabelProbability &src, HostLabelProbability &dst)
shared_ptr< OrganizedPlaneDetector > Ptr
HostLabelProbability P_l_host_
void setMpsAngularThreshold(double mpsAngularThreshold)
OrganizedPlaneDetector(int rows=480, int cols=640)
This is the constructor.
float getNeNormalSmoothingSize() const
HostLabelProbability P_l_host_prev_
void process(const PointCloud< PointTC >::ConstPtr &cloud)
Process step, this wraps Organized Plane Segmentation code.
pcl::OrganizedMultiPlaneSegmentation< PointTC, pcl::Normal, pcl::Label > mps_
double getMpsDistanceThreshold() const
bool mps_use_planar_refinement_
pcl::IntegralImageNormalEstimation< PointTC, pcl::Normal > ne_
int copyHostLabelProbability(HostLabelProbability &src, HostLabelProbability &dst)
Defines all the PCL implemented PointT point type structures.
Defines functions, macros and traits for allocating and using memory.
A point structure representing Euclidean xyz coordinates.
A point structure representing Euclidean xyz coordinates, and the RGBA color.