这个教程学习如何使用简单的滤波器，沿着指定维，过滤掉指定范围内外的值。
#include <iostream>#include <pcl/point_types.h>#include <pcl/filters/passthrough.h>int main (int argc, char** argv){ pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>); pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>); // Fill in the cloud data cloud->width = 5; cloud->height = 1; cloud->points.resize (cloud->width * cloud->height); for (size_t i = 0; i < cloud->points.size (); ++i) { cloud->points[i].x = 1024 * rand () / (RAND_MAX + 1.0f); cloud->points[i].y = 1024 * rand () / (RAND_MAX + 1.0f); cloud->points[i].z = 1024 * rand () / (RAND_MAX + 1.0f); } std::cerr << "Cloud before filtering: " << std::endl; for (size_t i = 0; i < cloud->points.size (); ++i) std::cerr << " " << cloud->points[i].x << " " << cloud->points[i].y << " " << cloud->points[i].z << std::endl; // Create the filtering object pcl::PassThrough<pcl::PointXYZ> pass; pass.setInputCloud (cloud); pass.setFilterFieldName ("z"); pass.setFilterLimits (0.0, 1.0); //pass.setFilterLimitsNegative (true); pass.filter (*cloud_filtered); std::cerr << "Cloud after filtering: " << std::endl; for (size_t i = 0; i < cloud_filtered->points.size (); ++i) std::cerr << " " << cloud_filtered->points[i].x << " " << cloud_filtered->points[i].y << " " << cloud_filtered->points[i].z << std::endl; return (0);}
一步一步来分析这些代码。
首先，我们创建一个PointCloud，填充数据。
然后创建一个直通滤波器并且设置参数。过滤器字段的名字设置为“Z”，接受的区间值设置为(0.0, 1.0)；
即：保留z轴上z值为0.0-1.0之间的值的点，其他点均过滤掉。
运行程序，你会看到类似如下的结果。
Cloud before filtering: 0.352222 -0.151883 -0.106395 -0.397406 -0.473106 0.292602 -0.731898 0.667105 0.441304 -0.734766 0.854581 -0.0361733 -0.4607 -0.277468 -0.916762Cloud after filtering: -0.397406 -0.473106 0.292602 -0.731898 0.667105 0.441304