ICP Registration

Summary

By setting benchmark point cloud and point cloud to be registered, perform the point cloud registration through ICP (Iterative Closest Points) algorithm. The basic steps of this algorithm are shown as follow.

Supposing that there are two given 3D-point collections, X1 and X2, the steps of ICP registration are shown as follows:

Step 1. For each point in X2, calculate and find its closest point in X1;

Step 2. Estimate the combination of rotation and translation using a root mean square point to point distance metric minimization technique which will best align each source point to its match found in the previous step.

Step 3. Transform X2 using the obtained transformation.

Step 4. Iterate the above steps until the average distance from X2 to X1 is less than a given threshold.

Usage

Click Data Management > Projections and Transformations > ICP Registration

Lidar360 Transform

Setting

  • Reference Cloud: The point cloud data will be used as benchmark for the registration. It can be inserted from outside or selected directly from the point cloud shown in the dropdown window.
  • Aligned Cloud: The point cloud to be registered. Users can choose one or more point cloud files need to be registered. Users can choose the aligned point cloud through the dropdown menu, and add, delete, or clear all the point clouds through the buttons ICP, ICP, or ICP next to the dropdown menu.
  • From Class: Choose the classes in the point cloud to be registered. All the classes are selected by default.
  • Use Selected Area: Users can select overlap area through the select tool in the LiDAR360 frame toolbox. If this option is selected, the registration will be performed only with the select area. If this option is not selected, the registration will be performed with the entire point cloud. It is recommended to select this option.
  • Number of Iterations (default value is "20"): The maximum times of iteration when performing the point cloud registration.
  • RMSE (default status is checked, default value is "1e-5"): Represent the difference in error between point clouds after current registration.
  • Number of Sample Points (default value is "50000"): If the number of points in the point cloud is larger than this threshold, randomly sample the threshold number of points to be registered.
  • Output Path: Output path for the registered point cloud data.

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