Precise Point Set Registration with Color Assisted and Correntropy for 3D Reconstruction

Teng Wan, Shaoyi Du, Yiting Xu, Guanglin Xu, Yang Yang, Yue Gao, Badong Chen

Abstract: Iterative closest point (ICP) algorithm, as its accuracy and efficiency, is widely used in rigid registration. However, ICP algorithm is easily failed when point sets lack of structure variety, such as semicircles. To solve this problem, a precise point set registration method for RGB-D data is proposed. Firstly, the color information provides a new information for registration, and the correntropy is introduced to deal with the noises and outliers. With color assisted and correntropy, a more robust objective function is built. Secondly, a variant ICP algorithm is used to deal with optimization problem via multiple iterations. Finally, as shown in the experimental results and scene reconstruction, our method obtains more precise results than other ICP algorithms.