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Cached k-d tree search for ICP algorithms

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3 Author(s)
Andreas Nuchter ; University of Osnabruck, Germany ; Kai Lingemann ; Joachim Hertzberg

The ICP (iterative closest point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, k-d trees have been used to accelerate the search. This paper presents a novel search procedure, namely cached k-d trees, exploiting iterative behavior of the ICP algorithm. It results in a significant speedup of about 50% as we show in an evaluation using different data sets.

Published in:

3-D Digital Imaging and Modeling, 2007. 3DIM '07. Sixth International Conference on

Date of Conference:

21-23 Aug. 2007