1 #ifndef OBJECT_RECOGNITION_H_
2 #define OBJECT_RECOGNITION_H_
6 #include "solution/filters.h"
7 #include "solution/segmentation.h"
8 #include "solution/feature_estimation.h"
9 #include "solution/registration.h"
11 #include <pcl/io/pcd_io.h>
12 #include <pcl/kdtree/kdtree_flann.h>
88 SurfaceNormalsPtr normals;
104 std::vector<pcl::PointIndices> cluster_indices;
108 PointCloudPtr largest_cluster (
new PointCloud);
111 return (largest_cluster);
117 SurfaceNormalsPtr & normals_out, PointCloudPtr & keypoints_out,
118 LocalDescriptorsPtr & local_descriptors_out, GlobalDescriptorsPtr & global_descriptor_out)
const
125 local_descriptors_out = computeLocalDescriptors (points, normals_out, keypoints_out,
128 global_descriptor_out = computeGlobalDescriptor (points, normals_out);
136 Eigen::Matrix4f tform;
143 tform = refineAlignment (source.
points, target.
points, tform,
154 std::vector<ObjectModel>
models_;
float local_descriptor_radius
float plane_inlier_distance_threshold
float initial_alignment_min_sample_distance
int outlier_rejection_min_neighbors
float keypoints_nr_scales_per_octave
float icp_max_correspondence_distance
float surface_normal_radius
GlobalDescriptorsPtr global_descriptor
float initial_alignment_max_correspondence_distance
void populateDatabase(const std::vector< std::string > &filenames)
PCL_EXPORTS void copyPointCloud(const pcl::PCLPointCloud2 &cloud_in, const std::vector< int > &indices, pcl::PCLPointCloud2 &cloud_out)
Extract the indices of a given point cloud as a new point cloud.
float outlier_rejection_radius
float downsample_leaf_size
void transformPointCloud(const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
Apply an affine transform defined by an Eigen Transform.
pcl::KdTreeFLANN< GlobalDescriptorT >::Ptr kdtree_
GlobalDescriptorsPtr descriptors_
float icp_outlier_rejection_threshold
ObjectRecognition(const ObjectRecognitionParameters ¶ms)
int max_ransac_iterations
LocalDescriptorsPtr local_descriptors
std::vector< ObjectModel > models_
float icp_transformation_epsilon
PointCloudPtr alignModelPoints(const ObjectModel &source, const ObjectModel &target, const ObjectRecognitionParameters ¶ms) const
float keypoints_min_scale
void constructObjectModel(const PointCloudPtr &points, ObjectModel &output) const
void estimateFeatures(const PointCloudPtr &points, const ObjectRecognitionParameters ¶ms, SurfaceNormalsPtr &normals_out, PointCloudPtr &keypoints_out, LocalDescriptorsPtr &local_descriptors_out, GlobalDescriptorsPtr &global_descriptor_out) const
float keypoints_nr_octaves
PointCloudPtr recognizeAndAlignPoints(const PointCloudPtr &query_cloud)
int initial_alignment_nr_iterations
float keypoints_min_contrast
PointCloudPtr applyFiltersAndSegment(const PointCloudPtr &input, const ObjectRecognitionParameters ¶ms) const
const ObjectModel & recognizeObject(const PointCloudPtr &query_cloud)
ObjectRecognitionParameters params_
boost::shared_ptr< KdTreeFLANN< PointT > > Ptr