PCL特征提取与匹配（3）：特征匹配问题解决

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使用2中的demo进行特征匹配，

1. keypoint-methods（关键点提取方法）使用Harris3D角点检测，
2. descriptor-types (特征点描述)使用FPFH
   运行到

   descriptor_kdtree.nearestKSearch(*source, i, k, k_indices, k_squared_distances);
   correspondences[i] = k_indices[0];
   

   遇到Assertion failed: point_representation_->isValid (point) && "Invalid (NaN, Inf) point coordinates given to nearestKSearch!", file C:\pcl-1.9.1\kdtree\include\pcl/kdtree/impl/kdtree_flann.hpp, line 136的错误

解决方法

1. 输出计算得到的特征描述子
   发现存在nan点

   printf("inf1");
   typename pcl::PointCloud<FeatureType>::iterator itr;
   for (itr = source->begin(); itr != source->end(); itr++)
   {
       std::cout << *itr << endl;
   }
   printf("inf2");
   
   (nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan)
   (1.43461, 0.68249, 7.00692, 5.67639, 0.586942, 14.6281, 1.97115, 50.7711, 13.3196, 2.07839, 1.84432, 0.0302716, 6.23244,5.27624, 2.1539, 10.8, 21.7394, 9.44449, 9.60597, 18.2812, 6.65871, 9.77746, 0.8217, 54.9463, 10.4616, 1.65747, 5.87402, 7.36899, 1.68395, 3.46515, 4.46561, 8.38836, 0.866902)
   ...    
   

2. 剔除nan点

PCL特征提取与匹配（3）：特征匹配问题解决

原文：https://www.cnblogs.com/procorosso/p/12695484.html