In this paper, we propose a new framework for segmentation and deformation estimation in texture-less point clouds. Given a reference point cloud and a corresponding deformed point cloud, our approach first segments both the point clouds using OBB-LBS (Oriented Bounding Box-Laplace Beltrami Spectral) and estimates the semi-global dense spectral shape descriptors. These coarse descriptors identify the segments which need to be further investigated for localizing the area of deformation at a finer level.
J. Kalyani, Vaiapury, K., and Dr. Latha Parameswaran, “A Spectral Approach for Segmentation and Deformation Estimation in Point Cloud Using Shape Descriptors”, in Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB), D. Pandian, Fernando, X., Baig, Z., and Shi, F., Eds. Cham: Springer International Publishing, 2019.