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typedef Feature< PointInT,
PointOutT >::PointCloudOut | PointCloudOut |
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typedef Feature< PointInT,
PointOutT >::PointCloudIn | PointCloudIn |
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| typedef pcl::PointCloud< PointNT > | PointCloudN |
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| typedef PointCloudN::Ptr | PointCloudNPtr |
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| typedef PointCloudN::ConstPtr | PointCloudNConstPtr |
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typedef boost::shared_ptr
< FeatureFromNormals< PointInT,
PointNT, PointOutT > > | Ptr |
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typedef boost::shared_ptr
< const FeatureFromNormals
< PointInT, PointNT, PointOutT > > | ConstPtr |
| |
| typedef PCLBase< PointInT > | BaseClass |
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typedef pcl::search::Search
< PointInT > | KdTree |
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typedef pcl::search::Search
< PointInT >::Ptr | KdTreePtr |
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typedef boost::function< int(size_t,
double, std::vector< int >
&, std::vector< float > &)> | SearchMethod |
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typedef boost::function< int(const
PointCloudIn &cloud, size_t
index, double, std::vector
< int > &, std::vector< float > &)> | SearchMethodSurface |
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| typedef pcl::PointCloud< PointInT > | PointCloud |
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| typedef PointCloud::Ptr | PointCloudPtr |
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| typedef PointCloud::ConstPtr | PointCloudConstPtr |
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| typedef PointIndices::Ptr | PointIndicesPtr |
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| typedef PointIndices::ConstPtr | PointIndicesConstPtr |
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| typedef pcl::PointCloud< PointRFT > | PointCloudLRF |
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| typedef PointCloudLRF::Ptr | PointCloudLRFPtr |
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| typedef PointCloudLRF::ConstPtr | PointCloudLRFConstPtr |
| |
|
| | SHOTColorEstimationOMP (bool describe_shape=true, bool describe_color=true, unsigned int nr_threads=-1) |
| | Empty constructor. More...
|
| |
| void | setNumberOfThreads (unsigned int nr_threads) |
| | Initialize the scheduler and set the number of threads to use. More...
|
| |
| virtual void | computePointSHOT (const int index, const std::vector< int > &indices, const std::vector< float > &sqr_dists, Eigen::VectorXf &shot) |
| | Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals. More...
|
| |
| void | setInputNormals (const PointCloudNConstPtr &normals) |
| | Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More...
|
| |
| PointCloudNConstPtr | getInputNormals () const |
| | Get a pointer to the normals of the input XYZ point cloud dataset. More...
|
| |
| void | setSearchSurface (const PointCloudInConstPtr &cloud) |
| | Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. More...
|
| |
| PointCloudInConstPtr | getSearchSurface () const |
| | Get a pointer to the surface point cloud dataset. More...
|
| |
| void | setSearchMethod (const KdTreePtr &tree) |
| | Provide a pointer to the search object. More...
|
| |
| KdTreePtr | getSearchMethod () const |
| | Get a pointer to the search method used. More...
|
| |
| double | getSearchParameter () const |
| | Get the internal search parameter. More...
|
| |
| void | setKSearch (int k) |
| | Set the number of k nearest neighbors to use for the feature estimation. More...
|
| |
| int | getKSearch () const |
| | get the number of k nearest neighbors used for the feature estimation. More...
|
| |
| void | setRadiusSearch (double radius) |
| | Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. More...
|
| |
| double | getRadiusSearch () const |
| | Get the sphere radius used for determining the neighbors. More...
|
| |
| void | compute (PointCloudOut &output) |
| | Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More...
|
| |
| void | computeEigen (pcl::PointCloud< Eigen::MatrixXf > &output) |
| | Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More...
|
| |
| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| | Provide a pointer to the input dataset. More...
|
| |
| PointCloudConstPtr const | getInputCloud () |
| | Get a pointer to the input point cloud dataset. More...
|
| |
| void | setIndices (const IndicesPtr &indices) |
| | Provide a pointer to the vector of indices that represents the input data. More...
|
| |
| void | setIndices (const IndicesConstPtr &indices) |
| | Provide a pointer to the vector of indices that represents the input data. More...
|
| |
| void | setIndices (const PointIndicesConstPtr &indices) |
| | Provide a pointer to the vector of indices that represents the input data. More...
|
| |
| void | setIndices (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols) |
| | Set the indices for the points laying within an interest region of the point cloud. More...
|
| |
| IndicesPtr const | getIndices () |
| | Get a pointer to the vector of indices used. More...
|
| |
| const PointInT & | operator[] (size_t pos) |
| | Override PointCloud operator[] to shorten code. More...
|
| |
| void | setInputReferenceFrames (const PointCloudLRFConstPtr &frames) |
| | Provide a pointer to the input dataset that contains the local reference frames of the XYZ dataset. More...
|
| |
| PointCloudLRFConstPtr | getInputReferenceFrames () const |
| | Get a pointer to the local reference frames. More...
|
| |
template<typename PointInT, typename PointNT, typename PointOutT = pcl::SHOT1344, typename PointRFT = pcl::ReferenceFrame>
class pcl::SHOTColorEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >
Definition at line 126 of file shot_omp.h.
template<typename PointInT , typename PointNT , typename PointOutT , typename PointRFT >
| void pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::computePointSHOT |
( |
const int |
index, |
|
|
const std::vector< int > & |
indices, |
|
|
const std::vector< float > & |
sqr_dists, |
|
|
Eigen::VectorXf & |
shot |
|
) |
| |
|
virtualinherited |
Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals.
- Parameters
-
| [in] | index | the index of the point in indices_ |
| [in] | indices | the k-neighborhood point indices in surface_ |
| [in] | sqr_dists | the k-neighborhood point distances in surface_ |
| [out] | shot | the resultant SHOT descriptor representing the feature at the query point |
Definition at line 988 of file shot.hpp.
template<typename PointInT , typename PointNT , typename PointOutT , typename PointRFT >
| void pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::RGB2CIELAB |
( |
unsigned char |
R, |
|
|
unsigned char |
G, |
|
|
unsigned char |
B, |
|
|
float & |
L, |
|
|
float & |
A, |
|
|
float & |
B2 |
|
) |
| |
|
staticinherited |
Converts RGB triplets to CIELab space.
- Parameters
-
| [in] | R | the red channel |
| [in] | G | the green channel |
| [in] | B | the blue channel |
| [out] | L | the lightness |
| [out] | A | the first color-opponent dimension |
| [out] | B2 | the second color-opponent dimension |
Definition at line 165 of file shot.hpp.
template<typename PointInT, typename PointNT, typename PointOutT>
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
In case of search surface is set to be different from the input cloud, normals should correspond to the search surface, not the input cloud!
- Parameters
-
| [in] | normals | the const boost shared pointer to a PointCloud of normals. By convention, L2 norm of each normal should be 1. |
Definition at line 351 of file feature.h.
template<typename PointInT , typename PointRFT >
Provide a pointer to the input dataset that contains the local reference frames of the XYZ dataset.
In case of search surface is set to be different from the input cloud, local reference frames should correspond to the input cloud, not the search surface!
- Parameters
-
| [in] | frames | the const boost shared pointer to a PointCloud of reference frames. |
Definition at line 471 of file feature.h.
template<typename PointInT, typename PointOutT>
Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset.
This is optional, if this is not set, it will only use the data in the input cloud to estimate the features. This is useful when you only need to compute the features for a downsampled cloud.
- Parameters
-
Definition at line 144 of file feature.h.
1.8.3.1