Octree索引(体素近邻搜索,K近邻搜索,半径内近邻搜索)------PCL
体素近邻搜索
/// <summary>
/// octree 体素近邻搜索
/// </summary>
/// <param name="cloud">索引点云</param>
/// <param name="searchPoint">索引点</param>
/// <param name="resolution">分辨率</param>
/// <returns>返回所有点编号数组</returns>
std::vector<int> PclTool::octreeVoxelSearch(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, const pcl::PointXYZ searchPoint, const float resolution)
{
pcl::octree::OctreePointCloudSearch<pcl::PointXYZ> octree(resolution); // 初始化Octree
octree.setInputCloud(cloud); // 设置输入点云
octree.addPointsFromInputCloud(); // 构建octree
std::vector<int> pointIdxVec; // 存储体素近邻搜索结果向量
if (octree.voxelSearch(searchPoint, pointIdxVec)) // 执行搜索
{
return pointIdxVec;
}
else
{
return std::vector<int>();
}
}
- 分辨率为:1
k紧邻搜索
std::vector<int> PclTool::octreeKSearch(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, const float resolution, const pcl::PointXYZ searchPoint, const unsigned int k)
{
pcl::octree::OctreePointCloudSearch<pcl::PointXYZ> octree(resolution); // 初始化Octree
octree.setInputCloud(cloud); // 设置输入点云
octree.addPointsFromInputCloud(); // 构建octree
std::vector<int> pointIdxNKNSearch; // 结果点的索引的向量
std::vector<float> pointNKNSquaredDistance; // 搜索点与近邻之间的距离的平方
if (octree.nearestKSearch(searchPoint, k, pointIdxNKNSearch, pointNKNSquaredDistance) > 0)
{
return pointIdxNKNSearch;
}
else
{
return std::vector<int>();
}
}
半径内近邻搜索
std::vector<int> PclTool::octreeRadiusSearch(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, const float resolution, const pcl::PointXYZ searchPoint, const float radius)
{
pcl::octree::OctreePointCloudSearch<pcl::PointXYZ> octree(resolution); // 初始化Octree
octree.setInputCloud(cloud); // 设置输入点云
octree.addPointsFromInputCloud(); // 构建octree
std::vector<int> pointIdxRadiusSearch;
std::vector<float> pointRadiusSquaredDistance;
if (octree.radiusSearch(searchPoint, radius, pointIdxRadiusSearch, pointRadiusSquaredDistance) > 0)
{
return pointIdxRadiusSearch;
}
else
{
return std::vector<int>();
}
}
原文地址:https://blog.csdn.net/mankeywang/article/details/137728164
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