A Method for Fast Search of Variable Regions on Dynamic 3D Point Clouds

The paper addresses the region search problem in three-dimensional (3D) space. The data used is a dynamically growing point cloud as it is typically gathered with a 3D-sensing device like a laser range-scanner. An encoding of space in combination with a new region search algorithm is introduced. The algorithm allows for fast access to spherical subsets of variable size. An octree based and a balanced binary tree based implementation are discussed. Finally, experiments concerning processing time are shown.