Title
Precise iterative closest point algorithm with corner point constraint for isotropic scaling registration
Abstract
The traditional iterative closest point (ICP) algorithm could register two point sets well, but it is easily affected by local dissimilarity. To deal with this problem, this paper proposes an isotropic scaling ICP algorithm with corner point constraint. First of all, because the corner points can preserve the similarity of the whole shapes, an objective function based on least square error is proposed under the guidance of the corner points. Second, a new ICP algorithm is proposed to complete the isotropic scaling registration. At each iterative step of this new algorithm, the correspondence is built based on the closest point searching, and then a closed-form solution of the transformation is computed. This new algorithm converges monotonically to a local minimum from any given initial scaling transformation. To obtain the expected minimum, the traditional scaling ICP algorithm is applied to compute the initial transformation. The experimental results demonstrate that our algorithm can prevent the influence of the local dissimilarity and improve the registration precision compared with the traditional ICP algorithm.
Year
DOI
Venue
2019
10.1007/s00530-017-0573-6
Multimedia Systems
Keywords
Field
DocType
Iterative closest point,Corner point,Isotropic scaling registration
Monotonic function,Point set registration,Computer science,Algorithm,Closest point,Least square error,Scaling,Iterative closest point
Journal
Volume
Issue
ISSN
25.0
SP2
1432-1882
Citations 
PageRank 
References 
2
0.42
16
Authors
7
Name
Order
Citations
PageRank
Shaoyi Du135740.68
Wenting Cui220.42
Liyang Wu320.42
Sirui Zhang461.48
Xuetao Zhang5696.90
Guanglin Xu6269.95
Meifeng Xu720.42