Point Cloud Library (PCL) 1.13.0
feature_estimation.h
1#pragma once
2
3#include "typedefs.h"
4
5#include <pcl/io/io.h>
6#include <pcl/features/normal_3d.h>
7#include <pcl/keypoints/sift_keypoint.h>
8#include <pcl/features/fpfh.h>
9#include <pcl/features/vfh.h>
10#include <pcl/search/kdtree.h>
11
12/* Use NormalEstimation to estimate a cloud's surface normals
13 * Inputs:
14 * input
15 * The input point cloud
16 * radius
17 * The size of the local neighborhood used to estimate the surface
18 * Return: A pointer to a SurfaceNormals point cloud
19 */
20SurfaceNormalsPtr
21estimateSurfaceNormals (const PointCloudPtr & input, float radius)
22{
25 normal_estimation.setRadiusSearch (radius);
26 normal_estimation.setInputCloud (input);
27 SurfaceNormalsPtr normals (new SurfaceNormals);
28 normal_estimation.compute (*normals);
29
30 return (normals);
31}
32
33/* Use SIFTKeypoint to detect a set of keypoints
34 * Inputs:
35 * points
36 * The input point cloud
37 * normals
38 * The input surface normals
39 * min_scale
40 * The smallest scale in the difference-of-Gaussians (DoG) scale-space
41 * nr_octaves
42 * The number of times the scale doubles in the DoG scale-space
43 * nr_scales_per_octave
44 * The number of scales computed for each doubling
45 * min_contrast
46 * The minimum local contrast that must be present for a keypoint to be detected
47 * Return: A pointer to a point cloud of keypoints
48 */
49PointCloudPtr
50detectKeypoints (const PointCloudPtr & points, const SurfaceNormalsPtr & /*normals*/,
51 float min_scale, int nr_octaves, int nr_scales_per_octave, float min_contrast)
52{
55 sift_detect.setScales (min_scale, nr_octaves, nr_scales_per_octave);
56 sift_detect.setMinimumContrast (min_contrast);
57 sift_detect.setInputCloud (points);
59 sift_detect.compute (keypoints_temp);
60 PointCloudPtr keypoints (new PointCloud);
61 pcl::copyPointCloud (keypoints_temp, *keypoints);
62
63 return (keypoints);
64}
65
66/* Use FPFHEstimation to compute local feature descriptors around each keypoint
67 * Inputs:
68 * points
69 * The input point cloud
70 * normals
71 * The input surface normals
72 * keypoints
73 * A cloud of keypoints specifying the positions at which the descriptors should be computed
74 * feature_radius
75 * The size of the neighborhood from which the local descriptors will be computed
76 * Return: A pointer to a LocalDescriptors (a cloud of LocalDescriptorT points)
77 */
78LocalDescriptorsPtr
79computeLocalDescriptors (const PointCloudPtr & points, const SurfaceNormalsPtr & normals,
80 const PointCloudPtr & keypoints, float feature_radius)
81{
84 fpfh_estimation.setRadiusSearch (feature_radius);
85 fpfh_estimation.setSearchSurface (points);
86 fpfh_estimation.setInputNormals (normals);
87 fpfh_estimation.setInputCloud (keypoints);
88 LocalDescriptorsPtr local_descriptors (new LocalDescriptors);
89 fpfh_estimation.compute (*local_descriptors);
90
91 return (local_descriptors);
92}
93
94/* Use VFHEstimation to compute a single global descriptor for the entire input cloud
95 * Inputs:
96 * points
97 * The input point cloud
98 * normals
99 * The input surface normals
100 * Return: A pointer to a GlobalDescriptors point cloud (a cloud containing a single GlobalDescriptorT point)
101 */
102GlobalDescriptorsPtr
103computeGlobalDescriptor (const PointCloudPtr & points, const SurfaceNormalsPtr & normals)
104{
107 vfh_estimation.setInputCloud (points);
108 vfh_estimation.setInputNormals (normals);
109 GlobalDescriptorsPtr global_descriptor (new GlobalDescriptors);
110 vfh_estimation.compute (*global_descriptor);
111
112 return (global_descriptor);
113}
114
115/* A simple structure for storing all of a cloud's features */
116struct ObjectFeatures
117{
118 PointCloudPtr points;
119 SurfaceNormalsPtr normals;
120 PointCloudPtr keypoints;
121 LocalDescriptorsPtr local_descriptors;
122 GlobalDescriptorsPtr global_descriptor;
123};
124
125/* Estimate normals, detect keypoints, and compute local and global descriptors
126 * Return: An ObjectFeatures struct containing all the features
127 */
129computeFeatures (const PointCloudPtr & input)
130{
131 ObjectFeatures features;
132 features.points = input;
133 features.normals = estimateSurfaceNormals (input, 0.05);
134 features.keypoints = detectKeypoints (input, features.normals, 0.005, 10, 8, 1.5);
135 features.local_descriptors = computeLocalDescriptors (input, features.normals, features.keypoints, 0.1);
136 features.global_descriptor = computeGlobalDescriptor (input, features.normals);
137
138 return (features);
139}
FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud d...
Definition: fpfh.h:79
void setInputNormals(const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
Definition: feature.h:339
void setSearchSurface(const PointCloudInConstPtr &cloud)
Provide a pointer to a dataset to add additional information to estimate the features for every point...
Definition: feature.h:146
void setRadiusSearch(double radius)
Set the sphere radius that is to be used for determining the nearest neighbors used for the feature e...
Definition: feature.h:198
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
Definition: feature.h:164
void compute(PointCloudOut &output)
Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using th...
Definition: feature.hpp:194
void compute(PointCloudOut &output)
Base method for key point detection for all points given in <setInputCloud (), setIndices ()> using t...
Definition: keypoint.hpp:137
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
Definition: keypoint.h:102
NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point.
Definition: normal_3d.h:244
void setInputCloud(const PointCloudConstPtr &cloud) override
Provide a pointer to the input dataset.
Definition: normal_3d.h:332
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition: pcl_base.hpp:65
SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset ...
Definition: sift_keypoint.h:94
void setMinimumContrast(float min_contrast)
Provide a threshold to limit detection of keypoints without sufficient contrast.
void setScales(float min_scale, int nr_octaves, int nr_scales_per_octave)
Specify the range of scales over which to search for keypoints.
VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud data...
Definition: vfh.h:73
void compute(PointCloudOut &output)
Overloaded computed method from pcl::Feature.
Definition: vfh.hpp:65
search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...
Definition: kdtree.h:62
shared_ptr< KdTree< PointT, Tree > > Ptr
Definition: kdtree.h:75
void copyPointCloud(const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out)
Copy all the fields from a given point cloud into a new point cloud.
Definition: io.hpp:142
PointCloudPtr points
LocalDescriptorsPtr local_descriptors
GlobalDescriptorsPtr global_descriptor
PointCloudPtr keypoints
SurfaceNormalsPtr normals