Point Cloud Computing for Rigid and Deformable 3D Object Recognition

摘要

This work develops several performant, robust and accurate algorithms for processing 3D data in industrial and robotic environments. Two fundamental challenges are solved: The fast localization of 3D points that neighbor a given query point and the detection of rigid and deformable objects in 3D point clouds and in multimodal data. Additionally, a fast and robust method for refining the position of two point clouds is presented and some fundamental algorithms regarding rotations are discussed.