12 #ifndef POINTCLOUD_REGISTRATION_H
13 #define POINTCLOUD_REGISTRATION_H
15 #include <pcl/common/common_headers.h>
35 const pointCloud::Ptr source
36 ,
const pointCloud::Ptr target
37 ,
double* fitness_score
50 Eigen::Matrix4d
icpLM(
51 const pointCloud::Ptr source
52 ,
const pointCloud::Ptr target
53 ,
double* fitness_score
54 ,
const double iterations);
98 pcl::PointCloud<pcl::FPFHSignature33>::Ptr
114 pointCloud::Ptr source
115 , pcl::PointCloud<pcl::FPFHSignature33>::Ptr source_descriptors
116 , pointCloud::Ptr target
117 , pcl::PointCloud<pcl::FPFHSignature33>::Ptr target_descriptors);
120 #endif // POINTCLOUD_REGISTRATION_H
void bilateralFiltering(pointCloud::Ptr organized_cloud)
Use bilateral filtering.
Eigen::Matrix4d icpLM(const pointCloud::Ptr source, const pointCloud::Ptr target, double *fitness_score, const double iterations)
Calls the pcl iterativeClosestPoint-algorithm levenberg-marquardt alternative (internally) ...
pcl::PointCloud< pcl::FPFHSignature33 >::Ptr fastPointFeatureHistogram(const pointCloud::Ptr input)
Extracts all (F)PFHs.
void movingLeastSquares(pointCloud::Ptr cloud)
Use moving least squares.
void covarianceDownsampling(pointCloud::Ptr cloud)
Use covariances for downsampling.
void computeSurfaceNormals(pointCloud::Ptr cloud)
Compute the surface normals.
void downsample(pointCloud::Ptr cloud)
Simple Voxel-Grid downsampling.
Eigen::Matrix4d initialAlignment(pointCloud::Ptr source, pcl::PointCloud< pcl::FPFHSignature33 >::Ptr source_descriptors, pointCloud::Ptr target, pcl::PointCloud< pcl::FPFHSignature33 >::Ptr target_descriptors)
Aligns the point-clouds initially using Sample Consensus.
Eigen::Matrix4d icp(const pointCloud::Ptr source, const pointCloud::Ptr target, double *fitness_score, const double iterations)
Calls the pcl iterativeClosestPoint-algorithm.
pcl::PointCloud< pcl::PointNormal > pointCloud
Typedef for shorter call of point-cloud-pointer-type.