Parallel evolutionary registration of range data

Authors:
Craig Robertson;Robert B. Fisher
Affiliations:
Vision Group, Institute for Action, Perception and Behaviour, Division of Informatics, University of Edinburgh, Edinburgh, United Kingdom EH1 2QL;Vision Group, Institute for Action, Perception and Behaviour, Division of Informatics, University of Edinburgh, Edinburgh, United Kingdom EH1 2QL
Venue:
Computer Vision and Image Understanding - Registration and fusion of range images
Year:
2002

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Abstract

Most range data registration techniques are variants on the iterative closest point (ICP) algorithm, proposed by Y. Chen and G. Medioni (1991, Proceedings of the IEEE Conference on Robotics and Automation) and P. J. Besl and N. D. McKay ( 1992, IEEE Trans. Pattern Anal. Mach. Intell. 14, 239-256). That algorithm, though, is only one approach to optimizing a least-squares point correspondence sum proposed by K. S. Arun. T. Huang, and S. D. Blostein (1987, IEEE Trans. Pattern Anal. Mach. Intell, 9, 698-700). In its basic form ICP has many problems, for example, its reliance on preregistration by hand close to the global minimum and its tendency to converge to suboptimal or incorrect solutions. This paper reports on an evolutionary registration algorithm which does not require initial prealignment and has a very broad basin of convergence. It searches many areas of a registration parameter space in parallel and has available to it a selection of evolutionary techniques to avoid local minima which plague both ICP and its variants.