Compute Point Cloud Convex Hull

This operator has two versions:

  • Compute Point Cloud Convex Hull : Processes point clouds without normal information.

  • Compute Point Cloud Convex Hull(with normal) : Processes point clouds with normal information.

Both have identical core functionality, only differing in the type of point cloud data they process. The output convex point cloud will retain the type of the input point cloud.

Functional Description

This operator computes the 3D convex hull for each input point cloud, outputting only the vertices that form the convex hull boundary (these vertices are part of the original input point cloud). The convex hull can be understood as the smallest convex polyhedron that encloses all points of the point cloud, much like an elastic band stretched tightly around the outermost points of the point cloud.

Usage Scenarios

  • Shape Simplification and Representation: Use fewer vertices (convex hull vertices) to represent the overall external contour and approximate shape of the point cloud.

  • Collision Detection Preprocessing: Using the convex hull of an object can greatly simplify calculations in collision detection.

  • Feature Extraction: The volume, surface area, number of vertices, etc., of the convex hull can serve as shape features for the point cloud.

  • Accelerating Subsequent Calculations: Before operations like calculating the minimum bounding box (AABB or OBB) of a point cloud, first computing the convex hull and then performing calculations on the convex hull vertices can significantly reduce the number of points involved in the calculation, improving efficiency, because the minimum bounding box of an object is the same as the minimum bounding box of its convex hull.

Inputs and Outputs

Input Items

Pointcloud: Input point cloud or list of point clouds.

Output Items

Convex point cloud: A list, where each element is a point cloud composed of the convex hull vertices of the corresponding input point cloud.