資源簡介
PCL教程,獲取PCD文件,點云濾波,可視化等

代碼片段和文件信息
//#include?
//#include?
//#include?
//#include?
//#include?
//
//int?main(int?argc?char**argv)
//{
// srand(time(NULL));
// //?創建一個PointCloudboost共享指針并進行實例化
// pcl::PointCloud::Ptr?cloud(new?pcl::PointCloud);
// //點云生成
// cloud->width?=?1000;
// cloud->height?=?1;
// cloud->points.resize(cloud->width?*?cloud->height);
// for?(size_t?i?=?0;?i?points.size();?++i)
// {
// cloud->points[i].x?=?1024.0f*?rand()?/?(RAND_MAX?+?1.0f);
// cloud->points[i].y?=?1024.0f*?rand()?/?(RAND_MAX?+?1.0f);
// cloud->points[i].z?=?1024.0f*?rand()?/?(RAND_MAX?+?1.0f);
// }
// pcl::KdTreeFLANNkdtree;?//?創建kd-tree對象
// kdtree.setInputCloud(cloud);???????????//?設置搜索空間
// //?定義查詢點并賦隨機值
// pcl::PointXYZ?searchPoint;
// searchPoint.x?=?1024.0f*?rand()?/?(RAND_MAX?+?1.0f);
// searchPoint.y?=?1024.0f*?rand()?/?(RAND_MAX?+?1.0f);
// searchPoint.z?=?1024.0f*?rand()?/?(RAND_MAX?+?1.0f);
// //?k近鄰搜索
// int?K?=?10;
// std::vectorpointIdxNKNSearch(K);??????????//?存儲查詢點近鄰索引
// std::vectorpointNKNSquaredDistance(K);??//?存儲近鄰點對應距離平方
// std::cout?<“K?nearest?neighbor?search?at?(“?<// <“?“?<// <“?“?<// <“)?with?K=“?<// //?執行k近鄰搜索
// if?(kdtree.nearestKSearch(searchPoint?K?pointIdxNKNSearch?pointNKNSquaredDistance)?>?0)
// {???//?打印出所有近鄰坐標
// for?(size_t?i?=?0;?i?// std::cout?<“????“?<points[pointIdxNKNSearch[i]].x
// <“?“?<points[pointIdxNKNSearch[i]].y
// <“?“?<points[pointIdxNKNSearch[i]].z
// <“?(squared?distance:?“?<// }
// //?在半徑r內搜索近鄰
// std::vector?pointIdxRadiusSearch;???????????//?存儲近鄰索引
// std::vector?pointRadiusSquaredDistance;???//?存儲近鄰對應的距離平方
// float?radius?=?256.0f*?rand()?/?(RAND_MAX?+?1.0f);
// std::cout?<“Neighbors?within?radius?search?at?(“?<// <“?“?<// <“?“?<// <“)?with?radius=“?<// if?(kdtree.radiusSearch(searchPoint?radius?pointIdxRadiusSearch?pointRadiusSquaredDistance)?>?0)
// {??//?如果kd-tree對象在指定半徑內返回多于0個近鄰,它將打印輸出向量中存儲的點的坐標與距離
// for?(size_t?i?=?0;?i?// std::cout?<“????“?<points[pointIdxRadiusSearch[i]].x
// <“?“?<points[pointIdxRadiusSearch[i]].y
// <“?“?<points[pointIdxRadiusSearch[i]].z
// <“?(squared?distance:?“?<// }
// return?0;
//}
?屬性????????????大小?????日期????時間???名稱
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?????文件???????2853??2016-11-21?14:52??新建文件夾\kd-tree\kdtree_search.cpp
?????文件???????2586??2016-11-23?11:14??新建文件夾\kd-tree\octree_change_detection.cpp
?????文件???????3432??2016-11-23?10:59??新建文件夾\kd-tree\octree_search.cpp
?????文件???????2546??2016-11-21?14:52??新建文件夾\kd-tree\源.cpp
?????文件???????1374??2016-12-07?11:04??新建文件夾\可視化\cloud_viewer.cpp
?????文件??????12935??2016-12-07?10:44??新建文件夾\可視化\pcl_visualizer_demo.cpp
?????文件???????5994??2016-11-23?17:07??新建文件夾\可視化\range_image_visualization.cpp
?????文件???????1754??2016-12-07?10:33??新建文件夾\濾波\1-Passthrough.cpp
?????文件???????1603??2016-12-07?15:56??新建文件夾\濾波\2-VoxelGrid.cpp
?????文件???????2011??2016-12-07?15:23??新建文件夾\濾波\3-StatisticalRemoval.cpp
?????文件???????2105??2016-12-14?11:21??新建文件夾\濾波\4-ProjectInliers.cpp
?????文件???????3454??2016-12-07?15:52??新建文件夾\濾波\5-ExtractIndices.cpp
?????文件???????2700??2016-12-07?17:12??新建文件夾\濾波\6-RemoveOutliers.cpp
?????文件???????3219??2016-11-18?11:16??新建文件夾\輸入輸出\concatenate_clouds.cpp
?????文件????????794??2016-11-17?16:32??新建文件夾\輸入輸出\pcd_read.cpp
?????文件????????931??2016-11-18?11:29??新建文件夾\輸入輸出\pcd_write.cpp
?????目錄??????????0??2016-12-16?14:40??新建文件夾\kd-tree
?????目錄??????????0??2016-12-16?14:40??新建文件夾\可視化
?????目錄??????????0??2016-12-16?14:39??新建文件夾\濾波
?????目錄??????????0??2016-12-16?14:40??新建文件夾\輸入輸出
?????目錄??????????0??2016-12-16?14:40??新建文件夾
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