@inproceedings{f8a7559808a745d7898d73c7bea29e19,
title = "Robust RGB-D Data Registration Based on Correntropy and Bi-directional Distance",
abstract = "The iterative closest point (ICP) algorithm is most widely used for rigid registration of point sets. In this paper, a robust ICP registration method data is proposed to register RGB-D data. Firstly, the color information is introduced to build more precise correspondence between two point sets. Secondly, to enhance the robustness of the algorithm to noise and outliers, the maximum correntropy criterion (MCC) is introduced to the registration framework. Thirdly, to reduce the possibility of the algorithm falling into local minimum and deal with ill-pose issue, the bidirectional distance measurement is added to the proposed algorithm. Finally, the experimental results of point sets registration and scene reconstruction demonstrate that the proposed algorithm can obtain more precise and robust results than other ICP algorithms.",
keywords = "Bi-directional distance, Correntropy, Point set registration, RGB-D data",
author = "Teng Wan and Shaoyi Du and Wenting Cui and Qixing Xie and Yuying Liu and Zuoyong Li",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 26th International Conference on MultiMedia Modeling, MMM 2020 ; Conference date: 05-01-2020 Through 08-01-2020",
year = "2020",
doi = "10.1007/978-3-030-37734-2\_26",
language = "英语",
isbn = "9783030377335",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "316--326",
editor = "Ro, \{Yong Man\} and Junmo Kim and Jung-Woo Choi and Wen-Huang Cheng and Wei-Ta Chu and Peng Cui and Min-Chun Hu and \{De Neve\}, Wesley",
booktitle = "MultiMedia Modeling - 26th International Conference, MMM 2020, Proceedings",
}