PCL汉明距离匹配代码

以下是PCL库中使用汉明距离进行匹配的示例代码：

#include <iostream>
#include <pcl/point_cloud.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/feature.h>
#include <pcl/features/fpfh.h>
#include <pcl/search/kdtree.h>

int main(int argc, char** argv) {
  // 读取两个点云
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud1(new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2(new pcl::PointCloud<pcl::PointXYZ>);
  pcl::io::loadPCDFile<pcl::PointXYZ>("cloud1.pcd", *cloud1);
  pcl::io::loadPCDFile<pcl::PointXYZ>("cloud2.pcd", *cloud2);

  // 计算FPFH特征
  pcl::FPFHEstimation<pcl::PointXYZ, pcl::FPFHSignature33> fpfh;
  fpfh.setInputCloud(cloud1);
  fpfh.setInputCloud(cloud2);
  pcl::PointCloud<pcl::FPFHSignature33>::Ptr fpfhs1(new pcl::PointCloud<pcl::FPFHSignature33>);
  pcl::PointCloud<pcl::FPFHSignature33>::Ptr fpfhs2(new pcl::PointCloud<pcl::FPFHSignature33>);
  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZ>);
  fpfh.setSearchMethod(tree);
  fpfh.setRadiusSearch(0.05);
  fpfh.compute(*fpfhs1);
  fpfh.compute(*fpfhs2);

  // 使用汉明距离进行匹配
  pcl::CorrespondencesPtr correspondences(new pcl::Correspondences);
  for (int i = 0; i < fpfhs1->size(); ++i) {
    int minIndex = -1;
    uint64_t minDistance = std::numeric_limits<uint64_t>::max();
    pcl::FPFHSignature33& target = fpfhs1->points[i];
    for (int j = 0; j < fpfhs2->size(); ++j) {
      pcl::FPFHSignature33& candidate = fpfhs2->points[j];
      uint64_t distance = 0;
      for (int k = 0; k < 33; ++k) {
        uint64_t diff = target.histogram[k] ^ candidate.histogram[k];
        while (diff) {
          ++distance;
          diff &= diff - 1;
        }
      }
      if (distance < minDistance) {
        minDistance = distance;
        minIndex = j;
      }
    }
    if (minIndex >= 0) {
      correspondences->push_back(pcl::Correspondence(i, minIndex, minDistance));
    }
  }

  // 输出匹配结果
  for (int i = 0; i < correspondences->size(); ++i) {
    pcl::Correspondence& correspondence = correspondences->at(i);
    std::cout << "correspondence " << i << ": cloud1[" << correspondence.index_query
              << "] <-> cloud2[" << correspondence.index_match << "] (distance: " << correspondence.distance
              << ")" << std::endl;
  }

  return 0;
}

这段代码读取了两个点云，使用FPFH特征描述子对它们进行特征提取，然后使用汉明距离进行匹配，并输出匹配结果。对于每个目标特征点，遍历所有候选特征点，计算它们的汉明距离，并选取距离最小的作为匹配点。最后将匹配结果存储在`pcl::CorrespondencesPtr`类型的指针中，每个匹配点包含两个点云中的点的索引和它们之间的距离。