ppf_helpers.hpp File Reference

#include <opencv2/core.hpp>

Namespaces
	cv
	cv::ppf_match_3d

Functions
Mat	cv::ppf_match_3d::addNoisePC (Mat pc, double scale)
void	cv::ppf_match_3d::computeBboxStd (Mat pc, float xRange[2], float yRange[2], float zRange[2])
int	cv::ppf_match_3d::computeNormalsPC3d (const Mat &PC, Mat &PCNormals, const int NumNeighbors, const bool FlipViewpoint, const double viewpoint[3])
	Compute the normals of an arbitrary point cloud computeNormalsPC3d uses a plane fitting approach to smoothly compute local normals. Normals are obtained through the eigenvector of the covariance matrix, corresponding to the smallest eigen value. If PCNormals is provided to be an Nx6 matrix, then no new allocation is made, instead the existing memory is overwritten. More...
void	cv::ppf_match_3d::destroyFlann (void *flannIndex)
void	cv::ppf_match_3d::getRandomPose (double Pose[16])
void *	cv::ppf_match_3d::indexPCFlann (Mat pc)
Mat	cv::ppf_match_3d::loadPLYSimple (const char *fileName, int withNormals)
	Load a PLY file. More...
Mat	cv::ppf_match_3d::normalize_pc (Mat pc, float scale)
Mat	cv::ppf_match_3d::normalizePCCoeff (Mat pc, float scale, float *Cx, float *Cy, float *Cz, float *MinVal, float *MaxVal)
void	cv::ppf_match_3d::queryPCFlann (void *flannIndex, Mat &pc, Mat &indices, Mat &distances)
Mat	cv::ppf_match_3d::samplePCByQuantization (Mat pc, float xrange[2], float yrange[2], float zrange[2], float sample_step_relative, int weightByCenter=0)
Mat	cv::ppf_match_3d::samplePCUniform (Mat PC, int sampleStep)
Mat	cv::ppf_match_3d::samplePCUniformInd (Mat PC, int sampleStep, std::vector< int > &indices)
Mat	cv::ppf_match_3d::transformPCPose (Mat pc, double Pose[16])
Mat	cv::ppf_match_3d::transPCCoeff (Mat pc, float scale, float Cx, float Cy, float Cz, float MinVal, float MaxVal)
void	cv::ppf_match_3d::writePLY (Mat PC, const char *fileName)
	Write a point cloud to PLY file. More...

Detailed Description

Author

Tolga Birdal <tbirdal AT gmail.com>