点云体素采样

体素采样主要是使用 VoxelGrid 这个函数，目的是大大降低处理的点云数量，同时保持点云的形状。

效果如下：

 设置叶子节点的尺寸 0.02

 

设置叶子节点0.05 

实现klib可视化平台的算子如下:

struct FilterVoxelGrid
{
	//VoxelGrid
	float leaf_x = 0.1;
	float leaf_y = 0.1;
	float leaf_z = 0.1;
	bool downsampleAllData = true;
	int min_points_per_voxel = 0;
	bool save_leaf_layout = false;
	double limit_min = -FLT_MAX;
	double limit_max = FLT_MAX;
	bool limit_negative = false;
	string filter_field_name;

	template<class PT>
	pcl::shared_ptr<PointCloud<PT>> operator()(const pcl::shared_ptr<PointCloud<PT> >& cloud)
	{
		pcl::shared_ptr<PointCloud<PT> > res(new PointCloud<PT>);
		VoxelGrid<PT> f;
		f.setInputCloud(cloud);
		f.setLeafSize(leaf_x, leaf_y, leaf_z);
		f.setDownsampleAllData(downsampleAllData);
		f.setMinimumPointsNumberPerVoxel(min_points_per_voxel);
		f.setSaveLeafLayout(save_leaf_layout);
		f.setFilterLimits(limit_min, limit_max);
		f.setFilterLimitsNegative(limit_negative);
		f.setFilterFieldName(filter_field_name);
		f.filter(*res);
		return res;
	}
};

struct KPclFilterVoxelGrid : KPlugBase
{
	FilterVoxelGrid p;
	
	KPclFilterVoxelGrid()
	{
		addProp("leaf_x").setType(PropTypeFloat).setValueAddr(&p.leaf_x);
		addProp("leaf_y").setType(PropTypeFloat).setValueAddr(&p.leaf_y);
		addProp("leaf_z").setType(PropTypeFloat).setValueAddr(&p.leaf_z);
		addProp("downsampleAllData").setType(PropTypeBool).setValueAddr(&p.downsampleAllData);
		addProp("min_points_per_voxel").setType(PropTypeInt32).setValueAddr(&p.min_points_per_voxel);
		addProp("save_leaf_layout").setType(PropTypeBool).setValueAddr(&p.save_leaf_layout);
		addProp("limit_min").setType(PropTypeDouble).setValueAddr(&p.limit_min);
		addProp("limit_max").setType(PropTypeDouble).setValueAddr(&p.limit_max);
		addProp("limit_negative").setType(PropTypeBool).setValueAddr(&p.limit_negative);
		addProp("filter_field_name").setType(PropTypeString).setValueAddr(&p.filter_field_name);
	}

	int __exec(const KArbit& src, KArbit& dst) override
	{
		dst = cld_op(src, p);
		return true;
	}
};