Improved Weight Iterative Closet Point Algorithm Applied in Point Cloud Registration
Abstract In this paper we aim to solve the problem that the traditional iterative closet point algorithm is not robust. Using the iterative closet point registration residuals law, the M-estimators and selecting weight iteration, an improved iterative closet point registration algorithm based on the weight of the point cloud is provided. In order to achieve protection against gross errors, using the residuals for each point on the registration calculation to calculate the corresponding initial weight, we use iteration method with variable weights to calculate suitable weight on the basis of additional points of weights. The experimental results indicate that proposed iteration method is capable of improving the effect of registration, and the improved algorithm is suitable for the registration of point cloud with gross errors.
Key words :
point cloud
registration
M-estimators
iteration method with variable weights
iterative closet point registration algorithm
Cite this article:
ZHANG Chongjun,XU Yezhang,ZHENG Shanxi et al. Improved Weight Iterative Closet Point Algorithm Applied in Point Cloud Registration[J]. jgg, 2019, 39(4): 417-420.
ZHANG Chongjun,XU Yezhang,ZHENG Shanxi et al. Improved Weight Iterative Closet Point Algorithm Applied in Point Cloud Registration[J]. jgg, 2019, 39(4): 417-420.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2019/V39/I4/417
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