Affine iterative closest point algorithm for point set registration

被引:201
作者
Du, Shaoyi [1 ]
Zheng, Nanning [1 ]
Ying, Shihui [2 ]
Liu, Jianyi [1 ]
机构
[1] Xi An Jiao Tong Univ, Inst Artificial Intelligence & Robot, Xian 710049, Peoples R China
[2] Shanghai Univ, Sch Sci, Dept Math, Shanghai 200444, Peoples R China
基金
中国国家自然科学基金;
关键词
Affine point set registration; Iterative closest point algorithm; Lie group; Singular value decomposition; Independent component analysis; ATLAS;
D O I
10.1016/j.patrec.2010.01.020
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
The traditional iterative closest point (ICP) algorithm is accurate and fast for rigid point set registration but it is unable to handle affine case. This paper instead introduces a novel generalized ICP algorithm based on lie group for affine registration of m-D point sets. First, with singular value decomposition technique applied, this paper decomposes affine transformation into three special matrices which are then constrained. Then, these matrices are expressed by exponential mappings of lie group and their Taylor approximations at each iterative step of affine ICP algorithm. In this way, affine registration problem is ultimately simplified to a quadratic programming problem. By solving this quadratic problem, the new algorithm converges monotonically to a local minimum from any given initial parameters. Hence, to reach desired minimum, good initial parameters and constraints are required which are successfully estimated by independent component analysis. This new algorithm is independent of shape representation and feature extraction, and thereby it is a general framework for affine registration of m-D point sets. Experimental results demonstrate its robustness and efficiency compared with the traditional ICP algorithm and the state-of-the-art methods. (c) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:791 / 799
页数:9
相关论文
共 38 条
[1]
2D and 3D face recognition: A survey [J].
Abate, Andrea F. ;
Nappi, Michele ;
Riccio, Daniel ;
Sabatino, Gabriele .
PATTERN RECOGNITION LETTERS, 2007, 28 (14) :1885-1906
[2]
Amberg B, 2007, IEEE I CONF COMP VIS, P1326
[3]
[Anonymous], 2006, P IEEE COMP SOC C CO
[4]
[Anonymous], POINT SET REGISTRATI
[5]
The Quickhull algorithm for convex hulls [J].
Barber, CB ;
Dobkin, DP ;
Huhdanpaa, H .
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 1996, 22 (04) :469-483
[6]
A METHOD FOR REGISTRATION OF 3-D SHAPES [J].
BESL, PJ ;
MCKAY, ND .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1992, 14 (02) :239-256
[7]
OBJECT MODELING BY REGISTRATION OF MULTIPLE RANGE IMAGES [J].
CHEN, Y ;
MEDIONI, G .
IMAGE AND VISION COMPUTING, 1992, 10 (03) :145-155
[8]
Chui H, 2004, IEEE T PATTERN ANAL, V26, P160, DOI 10.1109/TPAMI.2004.1262178
[9]
A new point matching algorithm for non-rigid registration [J].
Chui, HL ;
Rangarajan, A .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2003, 89 (2-3) :114-141
[10]
A reflective Newton method for minimizing a quadratic function subject to bounds on some of the variables [J].
Coleman, TF ;
Li, YY .
SIAM JOURNAL ON OPTIMIZATION, 1996, 6 (04) :1040-1058