Features

Low-level feature-extracting functions. More...

Functions
LocalDescriptorsPtr	map_merge_3d::computeLocalDescriptors (const PointCloudConstPtr &points, const SurfaceNormalsPtr &normals, const PointCloudPtr &keypoints, Descriptor descriptor, double feature_radius)
	Compute local feature descriptors around each keypoint. More...
SurfaceNormalsPtr	map_merge_3d::computeSurfaceNormals (const PointCloudConstPtr &input, double radius)
	Estimate cloud surface normals. More...
PointCloudPtr	map_merge_3d::detectKeypoints (const PointCloudConstPtr &points, const SurfaceNormalsPtr &normals, Keypoint type, double threshold, double radius, double resolution)
	Detects keypoints in the pointcloud. More...
PointCloudPtr	map_merge_3d::downSample (const PointCloudConstPtr &input, double resolution)
	Voxelize input pointcloud to reduce number of points. More...
DOXYGEN_SKIP	map_merge_3d::ENUM_CLASS (Descriptor, DESCRIPTORS_NAMES_)
	map_merge_3d::ENUM_CLASS (Keypoint, SIFT, HARRIS)
PointCloudPtr	map_merge_3d::removeOutliers (const PointCloudConstPtr &input, double radius, int min_neighbours)
	Removes outliers from the pointcloud. More...

Detailed Description

Low-level feature-extracting functions.

Low-level functions to extract features from pointclouds and to preprocess pointclouds for feature extraction. These function operate on individual pointcloud.

Function Documentation

computeLocalDescriptors()

LocalDescriptorsPtr map_merge_3d::computeLocalDescriptors	(	const PointCloudConstPtr &	points,
		const SurfaceNormalsPtr &	normals,
		const PointCloudPtr &	keypoints,
		Descriptor	descriptor,
		double	feature_radius
	)

Compute local feature descriptors around each keypoint.

If descriptors can not be computed to some of the keypoints, those keypoints will be removed from the keypoints cloud. Therefore the keypoints cloud can be also modified.

Parameters

points	input pointcloud
normals	input normals for the cloud
keypoints	input detected keypoints, where descriptors will be computed
descriptor	descriptor type to extract
feature_radius	search radius for descriptors

Returns

cloud of local descriptors

computeSurfaceNormals()

SurfaceNormalsPtr map_merge_3d::computeSurfaceNormals	(	const PointCloudConstPtr &	input,
		double	radius
	)

Estimate cloud surface normals.

Parameters

input	input cloud
radius	local neighbourhood size for estimating normals

Returns

cloud of computed normals

detectKeypoints()

PointCloudPtr map_merge_3d::detectKeypoints	(	const PointCloudConstPtr &	points,
		const SurfaceNormalsPtr &	normals,
		Keypoint	type,
		double	threshold,
		double	radius,
		double	resolution
	)

Detects keypoints in the pointcloud.

Normals are used only for geometric keypoints (HARRIS). SIFT keypoints requires valid colour information with points.

Parameters

points	input pointcloud
normals	normals for input
type	keypoint type to extract
threshold	determines how much keypoints to extract (corner measure)
radius	area used for keypoint detection around each point
resolution	smallest scale of the scale pyramid if the detector uses one

Returns

pointcloud of keypoints

downSample()

PointCloudPtr map_merge_3d::downSample	(	const PointCloudConstPtr &	input,
		double	resolution
	)

Voxelize input pointcloud to reduce number of points.

Parameters

input	input pointcloud
resolution	required resolution for voxelization

Returns

Voxelized pointcloud

ENUM_CLASS() [1/2]

DOXYGEN_SKIP map_merge_3d::ENUM_CLASS	(	Descriptor	,
		DESCRIPTORS_NAMES_
	)

ENUM_CLASS() [2/2]

map_merge_3d::ENUM_CLASS	(	Keypoint	,
		SIFT	,
		HARRIS
	)

removeOutliers()

PointCloudPtr map_merge_3d::removeOutliers	(	const PointCloudConstPtr &	input,
		double	radius,
		int	min_neighbours
	)

Removes outliers from the pointcloud.

Outliers with small number of neighbours will be removed.

Parameters

input	input pointcloud
radius	Area where neighbours will be counted
min_neighbours	Minimal number of neighbours for the point to be kept

Returns

filtered pointcloud