Title
Precise Point Set Registration With Color Assisted And Correntropy For 3d Reconstruction
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.
Year
DOI
Venue
2018
10.1109/SMC.2018.00673
2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
Keywords
Field
DocType
iterative closest point, RGB-D point set registration, color assisted, maximum correntropy criterion
Computer vision,Point set registration,Computer science,Outlier,Artificial intelligence,RGB color model,Optimization problem,Machine learning,3D reconstruction,Iterative closest point
Conference
ISSN
Citations 
PageRank 
1062-922X
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Teng Wan113.06
Shaoyi Du235740.68
Yiting Xu311.03
Guanglin Xu4269.95
Yang Yang585.51
Yue Gao63259124.70
Badong Chen791965.71