Reducing number of points for ICP algorithm based on geometrical properties

Dmitrii Tihonkih; Aleksei Voronin; Artyom Makovetskii; J. Diaz-Escobar

doi:10.1117/12.2321282

17 September 2018 Reducing number of points for ICP algorithm based on geometrical properties

Dmitrii Tihonkih, Aleksei Voronin, Artyom Makovetskii, J. Diaz-Escobar

Proceedings Volume 10752, Applications of Digital Image Processing XLI; 107522P (2018) https://doi.org/10.1117/12.2321282
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

ICP is the most commonly used algorithm in tasks of point clouds mapping, finding the transformation between clouds, building a three-dimensional map. One of the key steps of the algorithm is the removal a part of the points and the searching a correspondence of clouds. In this article, we propose a method for removing some points from the clouds. Reducing the number of points decrease an execution time of the next steps and, as a result, increase performance. The paper describes an approach based on the analysis of the geometric shapes of the scene objects. In the developed algorithm, the points lying on the boundaries of the planes intersections, the so-called edges of objects, are selected from the clouds. Then the intersection points of the found edges are checked to belong the main vertices of the objects. After that, additional vertices are excluded from the edges and, if necessary, new ones are added. The described approach is performed for both point clouds. All further steps of the ICP algorithm are performed with new clouds. In the next step, after finding the correspondence, the vertices found in the previous step are taken from the first cloud, with all the edges connected with them. For each such group it is necessary to find the corresponding group from the second cloud. The method looks for correspondence for geometrically similar parts of point clouds. After finding the intermediate transformation, the current error is calculated. The original point clouds are used for the error calculation. This approach significantly reduces the number of points participating the deciding of the ICP variational subproblem.

Citation Download Citation

Dmitrii Tihonkih, Aleksei Voronin, Artyom Makovetskii, and J. Diaz-Escobar "Reducing number of points for ICP algorithm based on geometrical properties", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522P (17 September 2018); https://doi.org/10.1117/12.2321282

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KEYWORDS

Clouds

Visualization

3D modeling

Algorithm development

Algorithms

Shape analysis

Computer science

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