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Point Cloud Library (PCL)
1.6.0
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Point Cloud Library (PCL)
1.6.0
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The pcl_filters library contains outlier and noise removal mechanisms for 3D point cloud data filtering applications.
An example of noise removal is presented in the figure below. Due to measurement errors, certain datasets present a large number of shadow points. This complicates the estimation of local point cloud 3D features. Some of these outliers can be filtered by performing a statistical analysis on each point's neighborhood, and trimming those which do not meet a certain criteria. The sparse outlier removal implementation in PCL is based on the computation of the distribution of point to neighbors distances in the input dataset. For each point, the mean distance from it to all its neighbors is computed. By assuming that the resulted distribution is Gaussian with a mean and a standard deviation, all points whose mean distances are outside an interval defined by the global distances mean and standard deviation can be considered as outliers and trimmed from the dataset.
Classes | |
| class | pcl::ApproximateVoxelGrid< PointT > |
| ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
| class | pcl::BilateralFilter< PointT > |
| A bilateral filter implementation for point cloud data. More... | |
| class | pcl::ConditionalRemoval< PointT > |
| ConditionalRemoval filters data that satisfies certain conditions. More... | |
| class | pcl::CropBox< PointT > |
| CropBox is a filter that allows the user to filter all the data inside of a given box. More... | |
| class | pcl::CropBox< sensor_msgs::PointCloud2 > |
| CropBox is a filter that allows the user to filter all the data inside of a given box. More... | |
| class | pcl::CropHull< PointT > |
| Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes. More... | |
| class | pcl::ExtractIndices< PointT > |
| ExtractIndices extracts a set of indices from a point cloud. More... | |
| class | pcl::ExtractIndices< sensor_msgs::PointCloud2 > |
| ExtractIndices extracts a set of indices from a point cloud. More... | |
| class | pcl::Filter< PointT > |
| Filter represents the base filter class. More... | |
| class | pcl::Filter< sensor_msgs::PointCloud2 > |
| Filter represents the base filter class. More... | |
| class | pcl::FilterIndices< PointT > |
| FilterIndices represents the base class for filters that are about binary point removal. More... | |
| class | pcl::FilterIndices< sensor_msgs::PointCloud2 > |
| FilterIndices represents the base class for filters that are about binary point removal. More... | |
| class | pcl::NormalSpaceSampling< PointT, NormalT > |
| NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point. More... | |
| class | pcl::PassThrough< PointT > |
| PassThrough passes points in a cloud based on constraints for one particular field of the point type. More... | |
| class | pcl::PassThrough< sensor_msgs::PointCloud2 > |
| PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More... | |
| class | pcl::ProjectInliers< PointT > |
| ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More... | |
| class | pcl::ProjectInliers< sensor_msgs::PointCloud2 > |
| ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More... | |
| class | pcl::RadiusOutlierRemoval< PointT > |
| RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have. More... | |
| class | pcl::RadiusOutlierRemoval< sensor_msgs::PointCloud2 > |
| RadiusOutlierRemoval is a simple filter that removes outliers if the number of neighbors in a certain search radius is smaller than a given K. More... | |
| class | pcl::RandomSample< PointT > |
| RandomSample applies a random sampling with uniform probability. More... | |
| class | pcl::RandomSample< sensor_msgs::PointCloud2 > |
| RandomSample applies a random sampling with uniform probability. More... | |
| class | pcl::StatisticalOutlierRemoval< PointT > |
| StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More... | |
| class | pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 > |
| StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More... | |
| class | pcl::VoxelGrid< PointT > |
| VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
| class | pcl::VoxelGrid< sensor_msgs::PointCloud2 > |
| VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
Functions | |
| template<typename PointT > | |
| void | pcl::removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, std::vector< int > &index) |
| Removes points with x, y, or z equal to NaN. | |
| template<typename PointT > | |
| void | pcl::removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, std::vector< int > &index) |
| Removes points with x, y, or z equal to NaN. | |
| Eigen::MatrixXi | pcl::getHalfNeighborCellIndices () |
| Get the relative cell indices of the "upper half" 13 neighbors. | |
| Eigen::MatrixXi | pcl::getAllNeighborCellIndices () |
| Get the relative cell indices of all the 26 neighbors. | |
| template<typename PointT > | |
| void | pcl::getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false) |
| Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin. | |
| Eigen::MatrixXi pcl::getAllNeighborCellIndices | ( | ) | [inline] |
Get the relative cell indices of all the 26 neighbors.
Definition at line 123 of file voxel_grid.h.
| Eigen::MatrixXi pcl::getHalfNeighborCellIndices | ( | ) | [inline] |
Get the relative cell indices of the "upper half" 13 neighbors.
Definition at line 86 of file voxel_grid.h.
| void pcl::getMinMax3D | ( | const typename pcl::PointCloud< PointT >::ConstPtr & | cloud, |
| const std::string & | distance_field_name, | ||
| float | min_distance, | ||
| float | max_distance, | ||
| Eigen::Vector4f & | min_pt, | ||
| Eigen::Vector4f & | max_pt, | ||
| bool | limit_negative = false |
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| ) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin.
| [in] | cloud | the point cloud data message |
| [in] | distance_field_name | the field name that contains the distance values |
| [in] | min_distance | the minimum distance a point will be considered from |
| [in] | max_distance | the maximum distance a point will be considered to |
| [out] | min_pt | the resultant minimum bounds |
| [out] | max_pt | the resultant maximum bounds |
| [in] | limit_negative | if set to true, then all points outside of the interval (min_distance;max_distace) are considered |
Definition at line 46 of file voxel_grid.hpp.
| void pcl::removeNaNFromPointCloud | ( | const pcl::PointCloud< PointT > & | cloud_in, |
| std::vector< int > & | index | ||
| ) |
Removes points with x, y, or z equal to NaN.
| cloud_in | the input point cloud |
| index | the mapping (ordered): cloud_out.points[i] = cloud_in.points[index[i]] |
Definition at line 45 of file filter_indices.hpp.
| void pcl::removeNaNFromPointCloud | ( | const pcl::PointCloud< PointT > & | cloud_in, |
| pcl::PointCloud< PointT > & | cloud_out, | ||
| std::vector< int > & | index | ||
| ) |
Removes points with x, y, or z equal to NaN.
| [in] | cloud_in | the input point cloud |
| [out] | cloud_out | the input point cloud |
| [out] | index | the mapping (ordered): cloud_out.points[i] = cloud_in.points[index[i]] |
Definition at line 45 of file filter.hpp.
1.7.6.1
