采样一致性算法主要是拟合点云中的平面、直线、圆等参数模型。
http://pointclouds.org/documentation/tutorials/random_sample_consensus.php#random-sample-consensus
平面拟合
将远离平面0.01米的点剔除掉
#include <pcl/sample_consensus/ransac.h>
#include <pcl/sample_consensus/sac_model_plane.h>
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr final(new pcl::PointCloud<pcl::PointXYZ>);
//创建一个平面模型
pcl::SampleConsensusModelPlane<pcl::PointXYZ>::Ptr
model_p(new pcl::SampleConsensusModelPlane<pcl::PointXYZ>(cloud));
//用于保存拟合后的点的索引
std::vector<int> inliers;
//创建随机采样一致性算法
pcl::RandomSampleConsensus<pcl::PointXYZ> ransac(model_p);
ransac.setDistanceThreshold(.01);
ransac.computeModel();
ransac.getInliers(inliers);
// copies all inliers of the model computed to another PointCloud
pcl::copyPointCloud (*cloud, inliers, *final);球形拟合
将远离qiu面0.01米的点剔除掉
#include <pcl/sample_consensus/ransac.h>
#include <pcl/sample_consensus/sac_model_sphere.h>
//用于保存拟合后的点的索引
std::vector<int> inliers;
// initialize PointClouds
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr final (new pcl::PointCloud<pcl::PointXYZ>);
// created RandomSampleConsensus object and compute the appropriated model
pcl::SampleConsensusModelSphere<pcl::PointXYZ>::Ptr
model_s(new pcl::SampleConsensusModelSphere<pcl::PointXYZ> (cloud));
pcl::RandomSampleConsensus<pcl::PointXYZ> ransac (model_s);
ransac.setDistanceThreshold (.01);
ransac.computeModel();
ransac.getInliers(inliers);
pcl::copyPointCloud (*cloud, inliers, *final);