LIE GROUP FRAMEWORK OF ITERATIVE CLOSEST POINT ALGORITHM FOR n-D DATA REGISTRATION

被引:17
作者
Ying, Shihui [1 ,2 ]
Peng, Jigen [1 ]
Du, Shaoyi [3 ]
Qiao, Hong [4 ]
机构
[1] Xi An Jiao Tong Univ, Inst Informat & Syst Sci, Fac Sci, Xian 710049, Peoples R China
[2] Shanghai Univ, Fac Sci, Dept Math, Shanghai 200444, Peoples R China
[3] Xi An Jiao Tong Univ, Inst Artificial Intelligence & Robot, Xian 710049, Peoples R China
[4] Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligent Sci, Beijing 100080, Peoples R China
关键词
ICP; Lie group; registration; iterative linear systems; initial parameters; NONRIGID REGISTRATION; MATRIX; ICP;
D O I
10.1142/S0218001409007533
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The iterative closet point (ICP) method is a dominant method for data registration that has attracted extensive attention. In this paper, a unified mathematical model of ICP based on Lie group representation is established. Under the framework, the registration problem is formulated into an optimization problem over a certain Lie group. In order to simplify the model and to reduce the dimension of parameter space, the translation part of geometric transformation is eliminated by calibrating the centers of two data sets under registration. As a result, a fast algorithm by solving an iterative linear system is designed for the optimization problem on Lie groups. Moreover, PCA and ICA methods are jointly applied to estimate the initial registration to achieve the global minimum. Finally, several illustrations and comparison experiments are presented to test the performance of the proposed algorithm.
引用
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页码:1201 / 1220
页数:20
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