Efficient integration of partial point clouds with few geometric features using improved colored ICP algorithm

Arisa Poonsri; Shogo Tokai

doi:10.1117/12.2625243

30 April 2022 Efficient integration of partial point clouds with few geometric features using improved colored ICP algorithm

Arisa Poonsri, Shogo Tokai

Author Affiliations +

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 1217728 (2022) https://doi.org/10.1117/12.2625243
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

Colored ICP is often used to integrate point clouds of objects with few geometric features. However, there are problems of convergence speed and local minima, and its performance depends on the point clouds' initial location. This paper proposes a method to deal with these problems by introducing texture smoothing and ICP’s parameter controls, which improves the conventional colored ICP. Our method improves the colored ICP algorithm by first focusing only on geometrical information with a large search range and gradually shifting to color information with a reduced search range to determine the particular location. We experiment on the simulated partial globe and the RGB-D object models as the models with few geometric features. We compare the performance of the different parameter controls and verify the effectiveness by measuring errors between transformed results and the ground truth. The experiment shows that our method improves the convergence of the models with insufficient geometric features by these adjusting parameter technique.

Citation Download Citation

Arisa Poonsri and Shogo Tokai "Efficient integration of partial point clouds with few geometric features using improved colored ICP algorithm", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 1217728 (30 April 2022); https://doi.org/10.1117/12.2625243

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