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Cited by 174

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Cached k-d tree search for ICP algorithms

Nuchter, Andreas, Lingemann, Kai, Hertzberg, Joachim·2007·Sixth International Conference on 3-D Digital Imaging and Modeling (3DIM 2007)

Abstract

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.

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Crossref · 10.1109/3dim.2007.15

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Metadata

Authors
Nuchter, A., Lingemann, K., & Hertzberg, J.
Venue
Sixth International Conference on 3-D Digital Imaging and Modeling (3DIM 2007)
Publisher
IEEE
Published
2007-08
Pages
419-426
ISSN
1550-6185 (ISSN-L)
OpenAlex
W2096877058
Cited by
174
References
2
FWCI
12.10
Type
conference paper
Language
en
Open access
closed

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