Point Cloud Library (PCL)
1.9.1
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39 #ifndef PCL_FEATURES_LINEAR_LEAST_SQUARES_NORMAL_H_
40 #define PCL_FEATURES_LINEAR_LEAST_SQUARES_NORMAL_H_
42 #include <pcl/point_cloud.h>
44 #include <pcl/features/feature.h>
51 template <
typename Po
intInT,
typename Po
intOutT>
55 typedef boost::shared_ptr<LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >
Ptr;
56 typedef boost::shared_ptr<const LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >
ConstPtr;
66 use_depth_dependent_smoothing_(false),
67 max_depth_change_factor_(1.0f),
68 normal_smoothing_size_(9.0f)
93 normal_smoothing_size_ = normal_smoothing_size;
102 use_depth_dependent_smoothing_ = use_depth_dependent_smoothing;
112 max_depth_change_factor_ = max_depth_change_factor;
137 bool use_depth_dependent_smoothing_;
140 float max_depth_change_factor_;
143 float normal_smoothing_size_;
147 #ifdef PCL_NO_PRECOMPILE
148 #include <pcl/features/impl/linear_least_squares_normal.hpp>
This file defines compatibility wrappers for low level I/O functions.
PointCloudConstPtr input_
The input point cloud dataset.
void computeFeature(PointCloudOut &output)
Computes the normal for the complete cloud.
boost::shared_ptr< const LinearLeastSquaresNormalEstimation< PointInT, PointOutT > > ConstPtr
void setDepthDependentSmoothing(bool use_depth_dependent_smoothing)
Set whether to use depth depending smoothing or not.
Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
LinearLeastSquaresNormalEstimation()
Constructor.
virtual ~LinearLeastSquaresNormalEstimation()
Destructor.
void setNormalSmoothingSize(float normal_smoothing_size)
Set the normal smoothing size.
virtual void setInputCloud(const typename PointCloudIn::ConstPtr &cloud)
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
void setMaxDepthChangeFactor(float max_depth_change_factor)
The depth change threshold for computing object borders.
KdTreePtr tree_
A pointer to the spatial search object.
Feature< PointInT, PointOutT >::PointCloudIn PointCloudIn
Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylo...
int k_
The number of K nearest neighbors to use for each point.
boost::shared_ptr< const PointCloud< PointInT > > ConstPtr
std::string feature_name_
The feature name.
void computePointNormal(const int pos_x, const int pos_y, PointOutT &normal)
Computes the normal at the specified position.
boost::shared_ptr< LinearLeastSquaresNormalEstimation< PointInT, PointOutT > > Ptr
Feature represents the base feature class.