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...
默认情况下,registration_icp运行直到收敛或达到最大迭代次数(默认为30)。可以更改它以允许更多的计算时间并进一步改善结果。 reg_p2p = o3d.registration.registration_icp(source, target, threshold, trans_init, o3d.registration.TransformationEstimationPointToPoint(), o3d.registration.ICPConvergenceCriteria(max_it...
点云的粗配准(coarse registration)是指通过快速但不精确的方法,对两个点云进行初步对齐,使它们的大致位置和方向一致;精配准(fine registration)则是在粗配准的基础上,使用精确但计算量较大的算法,如ICP(Iterative Closest Point),对点云进行细致调整,以达到高精度的对齐。 点云配准的本质是通过几何变换(包括旋转、...
def demo_manual_registration(): print("手动ICP演示") # 加载点云 source = o3d.io.read_point_cloud("../../test_data/ICP/cloud_bin_0.pcd") target = o3d.io.read_point_cloud("../../test_data/ICP/cloud_bin_2.pcd") print("手动对齐前两点云的可视化") draw_registration_result(source...
reg_p2p = o3d.pipelines.registration.registration_icp(source, target, threshold, trans_init, o3d.pipelines.registration.TransformationEstimationPointToPoint(), o3d.pipelines.registration.ICPConvergenceCriteria(max_iteration=4000))这是调用 ICP 配准的主要函数,它返回一个RegistrationResult对象,包含了配准的结果...
o3d.utility.Vector2iVector(corr))# point-to-point ICP for refinementprint("Perform point-to-point ICP refinement") threshold =0.03# 3cm distance thresholdreg_p2p = o3d.pipelines.registration.registration_icp( source, target, threshold, trans_init, ...
registration_generalized_icp(): incompatiblefunctionarguments.The following argument types are supported: 1. (source: open3d.cuda.pybind.geometry.PointCloud, target: open3d.cuda.pybind.geometry.PointCloud, max_correspondence_distance: float, init: numpy.ndarray[numpy.float64[4, 4]]=array([[1., ...
def refine_registration(source, target, source_fpfh, target_fpfh, voxel_size): distance_threshold = voxel_size * 0.4 print(":: 对原始点云进行点对面ICP配准精细对齐, 这次使用严格的距离阈值: %.3f." % distance_threshold) result = o3d.pipelines.registration.registration_icp(source, target, distan...
o3d.registration.ICPConvergenceCriteria(max_iteration=200)) trans_init=trans.transformation pcd1.transform(trans_init) 此代码将执行迭代最近点对(ICP)算法以将多个视角的点云配准到同一坐标系中。结果是每个点云被变换以对齐到参考帧。 将所有点云合并到单个模型中 ...
doubleth =0.02;open3d::registration::RegistrationResult res = open3d::registration::RegistrationICP(source, target, th, Eigen::Matrix4d::Identity(),TransformationEstimationPointToPoint(false), ICPConvergenceCriteria(1e-6,1e-6,300));//显示配准结果 fitness 算法对这次...