1.计算点云最近点的平均距离（点云的平均距离）

1 double computeCloudResolution (const pcl::PointCloud
     
      ::ConstPtr &cloud) 2 { 3   double res = 0.0; 4   int n_points = 0; 5   int nres; 6   std::vector
      
        indices (2); 7   std::vector
       
         sqr_distances (2); 8   pcl::search::KdTree
        
          tree; 9   tree.setInputCloud (cloud);10 11   for (size_t i = 0; i < cloud->size (); ++i)12   {13     if (! pcl_isfinite ((*cloud)[i].x))14     {15       continue;16     }17     //Considering the second neighbor since the first is the point itself.18     nres = tree.nearestKSearch (i, 2, indices, sqr_distances);19     if (nres == 2)20     {21       res += sqrt (sqr_distances[1]);22       ++n_points;23     }24   }25   if (n_points != 0)26   {27     res /= n_points;28   }29   return res;30 }
        
       
      
     

 

1 assert(m_app); 2     if (!m_app) 3         return; 4  5     const ccHObject::Container& selectedEntities = m_app->getSelectedEntities(); 6     size_t selNum = selectedEntities.size(); 7     if (selNum!=1) 8     { 9         m_app->dispToConsole("Select only one cloud!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);10         return;11     }12 13     ccHObject* ent = selectedEntities[0];14     assert(ent);15     if (!ent || !ent->isA(CC_TYPES::POINT_CLOUD))16     {17         m_app->dispToConsole("Select a real point cloud!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);18         return;19     }20 21     ccPointCloud* m_cc_cloud = static_cast
      
       (ent);22 23     //input cloud24     unsigned count = m_cc_cloud->size();25     bool hasNorms = m_cc_cloud->hasNormals();26     CCVector3 bbMin, bbMax;27     m_cc_cloud->getBoundingBox(bbMin,bbMax);28     const CCVector3d& globalShift = m_cc_cloud->getGlobalShift();29     double globalScale = m_cc_cloud->getGlobalScale();30 31     pcl::PointCloud
       
        ::Ptr pcl_cloud (new pcl::PointCloud
        
         );32     try33     {34         unsigned pointCount = m_cc_cloud->size();35         pcl_cloud->resize(pointCount);36 37         for (unsigned i = 0; i < pointCount; ++i)38         {39             const CCVector3* P = m_cc_cloud->getPoint(i);40             pcl_cloud->at(i).x = static_cast
         
          (P->x);41             pcl_cloud->at(i).y = static_cast
          
           (P->y);42             pcl_cloud->at(i).z = static_cast
           
            (P->z);43 }44 }45 catch(...)46 {47 //any error (memory, etc.)48 pcl_cloud.reset();49 }50 if (!target_indices_ || target_indices_->size () == 0)51 {52 target_indices_.reset (new std::vector 
            
              (static_cast 
             
               (pcl_cloud->size ())));53 int index = 0;54 for (std::vector 
              
               ::iterator it = target_indices_->begin (), it_e = target_indices_->end (); it != it_e; it++)55 *it = index++;56 }57 Eigen::Vector4f pt_min, pt_max;58 pcl::getMinMax3D (*pcl_cloud, *target_indices_, pt_min, pt_max);59 double diameter_ = (pt_max - pt_min).norm ();//点云中最远的两个点的距离60 double dis=computeCloudResolution(pcl_cloud);61 m_app->dispToConsole(QString("cross distance (c=%1)\nmean distance(m=%2)").arg(diameter_,0,'f').arg(dis,0,'f'),ccMainAppInterface::STD_CONSOLE_MESSAGE);