cloudViewer.t.pipelines.registration.multi_scale_icp

cloudViewer.t.pipelines.registration.multi_scale_icp(source, target, voxel_sizes, criteria_list, max_correspondence_distances, init_source_to_target=[[1 0 0 0], [0 1 0 0], [0 0 1 0], [0 0 0 1]] Tensor[shape={4, 4}, stride={4, 1}, Float64, , estimation_method=TransformationEstimationPointToPoint, callback_after_iteration=None)

Function for Multi-Scale ICP registration

Parameters:

• source (cloudViewer::t::geometry::PointCloud) – The source point cloud.

• target (cloudViewer::t::geometry::PointCloud) – The target point cloud.

• voxel_sizes (cloudViewer.utility.DoubleVector) – o3d.utility.DoubleVector of voxel sizes in strictly decreasing order, for multi-scale icp.

• criteria_list (collections.abc.Sequence[cloudViewer.t.pipelines.registration.ICPConvergenceCriteria]) – List of Convergence criteria for each scale of multi-scale icp.

• max_correspondence_distances (cloudViewer.utility.DoubleVector) – o3d.utility.DoubleVector of maximum correspondence points-pair distances for multi-scale icp.

• init_source_to_target (cloudViewer.core.Tensor, optional, default=[[1 0 0 0], [0 1 0 0], [0 0 1 0], [0 0 0 1]] Tensor[shape={4, 4}, stride={4, 1}, Float64) – Initial transformation estimation ()

• estimation_method (cloudViewer.t.pipelines.registration.TransformationEstimation, optional, default=TransformationEstimationPointToPoint) – Estimation method. One of (TransformationEstimationPointToPoint, TransformationEstimationPointToPlane, TransformationEstimationForColoredICP, TransformationEstimationForGeneralizedICP)

• callback_after_iteration (collections.abc.Callable[[collections.abc.Mapping[str, cloudViewer.core.Tensor]], None], optional, default=None) – Optional lambda function, saves string to tensor map of attributes such as iteration_index, scale_index, scale_iteration_index, inlier_rmse, fitness, transformation, on CPU device, updated after each iteration.

Returns:

cloudViewer.t.pipelines.registration.RegistrationResult