大型点云场景,直接ICP会耗费很大的内存和时间,这里人工提取关键点,将关键点位移配准到关键点,即可得到旋转矩阵,然后作为大点云的旋转矩阵。 Open3d 关键点ICP,人工提点后的一个简单的ICP 前言 ICP算法有很多;Open3d自带的全局快速注册execute_fast_global_registration可以计算FPFH特征,快速对齐点云,这里不做介绍,当你...
target_fpfh, voxel_size):distance_threshold = voxel_size *0.5print(":: Apply fast global registration with distance threshold %.3f"\% distance_threshold)result = o3d.registration.registration_fast_based_on_feature_matching(source_down, target_down, source_fpfh, target_fpfh,o3d.registration.Fast...
PreprocessPointCloud("../data/fragment1.ply", voxel_size); pipelines::registration::RegistrationResult registration_result = pipelines::registration:: FastGlobalRegistrationBasedOnFeatureMatching( *source_down, *target_down, *source_fpfh, *target_fpfh, pipelines::registration:: FastGlobalRegistrationOption...
def execute_global_registration(source_down, target_down, source_fpfh,target_fpfh, voxel_size):distance_threshold = voxel_size *1.5print(":: RANSAC registration on downsampled point clouds.")print(" Since the downsampling voxel size is %.3f,"% voxel_size)print...
GlobalOptimizationOption定于了两个参数。max_correspondence_distance定义了对应阈值。edge_prune_threshold是修剪异常边缘的阈值。reference_node是被视为全局空间的节点ID。 代码语言:javascript 复制 print("Optimizing PoseGraph ...")option=o3d.registration.GlobalOptimizationOption(max_correspondence_distance=max_corre...
Prior to a local registration we need some kind of global registration. This family of algorithms do not require an alignment for initialization. They usually produce less tight alignment results and are used as initialization of the local methods. This notebook deals with the local registration ...
#include "Open3D/Registration/FastGlobalRegistration.h" using namespace open3d; using namespace std; using namespace registration; using namespace geometry; using namespace cv; void main() { open3d::geometry::PointCloud source, target;
openni_grabber registration open3d_colored_icp.py open3d_fast_global_registration.py open3d_global_registration.py open3d_icp.py pcl_icp.cpp pcl_template_matching.cpp sample_consensus segmentation trees CMakeLists.txt README.mdBreadcrumbs pointcloud_tutorial /registration / open3d_icp.py Latest...
pose_graph = full_registration(pcds_down, max_correspondence_distance_coarse, max_correspondence_distance_fine) Open3D使用global_optimization 功能执行姿势图优化。有两种优化方法可供选择:GlobalOptimizationGaussNewton or GlobalOptimizationLevenbergMarquardt。推荐后者,因为它具有更好的收敛性。类GlobalOptimizationConv...
Open3D 提供了函数 evaluate_registration 进行点云配准,输入前一帧的点云和当前帧的点云以及前一帧的位置参数。 evaluation = o3d.pipelines.registration.evaluate_registration( source, target, threshold, trans_init) 函数会返回两个值:fitness 用来衡量重叠区域即配准程度,越大越好;inlier_rmse 用来表示正确点的...