PCL高斯滤波两种方法：pcl::filters::GaussianKernel和pcl::filter::Convolution使用的报错问题_pcl::gaussiankernel

想调用ｐｃｌ高斯滤波函数进行点云处理中，先参考了两种网上的ｐｃｌ高斯滤波程序，在ＶＳ２０１３中运行报错，一直未能解决，求助！！！

方法1：（参考文章：https://blog.csdn.net/fandq1223/article/details/53183489）

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/filters/convolution_3d.h>
#include <pcl/filters/convolution.h>
#include <pcl/search/kdtree.h>
 
int main(int argc, char** argv)
{
	pcl::PointCloud<pcl::PointXYZ>::Ptr inputCloud(new pcl::PointCloud<pcl::PointXYZ>);
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
 
	if (pcl::io::loadPCDFile("test.pcd", *inputCloud) == -1)
	{
		PCL_ERROR("Couldn't read file test_pcd.pcd\n");
		return(-1);
	}
	pcl::filters::Convolution<pcl::PointXYZ, pcl::PointXYZ>  convolution;
	Eigen::ArrayXf gaussian_kernel(5);
	gaussian_kernel << 1.f / 16, 1.f / 4, 3.f / 8, 1.f / 4, 1.f / 16;
	convolution.setBordersPolicy(
	pcl::filters::Convolution<pcl::PointXYZ, pcl::PointXYZ>::BORDERS_POLICY_IGNORE);
	convolution.setDistanceThreshold(static_cast<float> (0.1));
	convolution.setInputCloud(inputCloud);
	convolution.setKernel(gaussian_kernel);
	convolution.convolve(*cloud);
}

运行到最后一句convolution.convolve(*cloud);时报错：，尝试修改程序，任然报错

方法2：（参考文章：https://blog.csdn.net/fandq1223/article/details/53183489）

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/filters/convolution_3d.h>
#include <pcl/filters/convolution.h>
#include <pcl/search/kdtree.h>
 
int main(int argc, char** argv)
{
 
	//Create the input and filtered cloud objects
	pcl::PointCloud<pcl::PointXYZ>::Ptr inputcloud(new pcl::PointCloud<pcl::PointXYZ>);
	pcl::PointCloud<pcl::PointXYZ>::Ptr outputcloud(new pcl::PointCloud<pcl::PointXYZ>);
 
	//Read in the input file
	if (pcl::io::loadPCDFile("test.pcd", *inputcloud) == -1)
	{
		PCL_ERROR("Couldn't read file test_pcd.pcd\n");
		return(-1);
	}
 
	//Set up the Gaussian Kernel
	pcl::filters::GaussianKernel<pcl::PointXYZ, pcl::PointXYZ>::Ptr kernel(new pcl::filters::GaussianKernel<pcl::PointXYZ, pcl::PointXYZ>);
	(*kernel).setSigma(4);
	(*kernel).setThresholdRelativeToSigma(4);
	std::cout << "Kernel made" << std::endl;
 
	//Set up the KDTree
	pcl::search::KdTree<pcl::PointXYZ>::Ptr kdtree(new pcl::search::KdTree<pcl::PointXYZ>);
	(*kdtree).setInputCloud(inputcloud);
	std::cout << "KdTree made" << std::endl;
 
	//Set up the Convolution Filter
	pcl::filters::Convolution3D<pcl::PointXYZ, pcl::PointXYZ, pcl::filters::GaussianKernel<pcl::PointXYZ, pcl::PointXYZ>> convolution;
	convolution.setKernel(*kernel);
	convolution.setInputCloud(inputcloud);
	convolution.setSearchMethod(kdtree);
	convolution.setRadiusSearch(100);
	std::cout << "Convolution Start" << std::endl;
 
	convolution.convolve(*outputcloud);
	std::cout << "Convoluted" << std::endl;
 
}

在生成解决方案时对数第二句convolution.convolve(*outputcloud);报错：error C3066：使用这些参数调用此类型的对象有多种方法，查找资料也未能解决。