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Affine iterative closest point algorithm for point set registration
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AI
DOI：10.1016/j.patrec.2010.01.020.png)
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Abstract
En 中文
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.
Keywords:
Affine point set registration
Iterative closest point algorithm
Lie group
Singular value decomposition
Independent component analysis
Journal
IF:
3.3
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7.8K
Citations:
1.6W