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Pattern Recognition 37 (2004) 15671571 www.elsevier.com/locate/patcog

Summary: Pattern Recognition 37 (2004) 1567­1571
Rapid and Brief Communication
Gaussian ˙elds: a new criterion for 3D rigid registration
Faysal Boughorbel, Andreas Koschan, Besma Abidi, Mongi Abidi
Imaging, Robotics and Intelligent Systems Laboratory, Electrical and Computer Engineering Department, University of Tennessee,
Knoxville, TN 37996, USA
Received 4 February 2004; accepted 10 February 2004
This paper introduces a new and simple criterion for rigid registration based on Gaussian ˙elds. The criterion is always
di erentiable and convex in a large neighborhood of the alignment parameters; allowing for the use of well-proven optimization
techniques. Using this method we can extend the size of the region of convergence so that no close initialization is needed, thus
overcoming local convergence problems of Iterative Closest Point algorithms. Furthermore, the Gaussian energy function can
be evaluated with linear complexity using the fast Gauss transform, which permits e cient implementation of the registration
algorithm. Experimental analysis on real-world data sets shows the usefulness and points the limits of the approach.
? 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Keywords: Rigid registration; Gaussian ˙elds; Moment invariants; Fast Gauss transform; Optimization
1. Introduction
The registration of range maps, and in general of 3D free
form surfaces, is an important task in many computer vision


Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee


Collections: Computer Technologies and Information Sciences