%0 Conference Paper %1 3DIM2007 %A Nüchter, A. %A Lingemann, K. %A Hertzberg, J. %B Proceedings of the 6th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '07) %C Montreal, QC, Canada %D 2007 %K imported myown %P 419--426 %R 10.1109/3DIM.2007.15 %T Cached $k$-d tree search for ICP Algorithms %U https://robotik.informatik.uni-wuerzburg.de/telematics/download/3dim2007.pdf %X 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.

@inproceedings{3DIM2007, 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.}, added-at = {2017-09-19T13:40:53.000+0200}, address = {Montreal, QC, Canada}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, biburl = {https://www.bibsonomy.org/bibtex/217548272493c6c411f9ac67993d7474b/nuechter76}, booktitle = {Proceedings of the 6th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '07)}, doi = {10.1109/3DIM.2007.15}, interhash = {a580d91115e678f00bee387941ba2af7}, intrahash = {17548272493c6c411f9ac67993d7474b}, keywords = {imported myown}, month = {August}, pages = {419--426}, timestamp = {2024-07-30T17:50:01.000+0200}, title = {{C}ached $k$-d tree search for {ICP} {A}lgorithms}, url = {https://robotik.informatik.uni-wuerzburg.de/telematics/download/3dim2007.pdf}, year = 2007 }