Filtering the outliers from backpack mobile laser scanning data
Author(s) -
Petri Rönnholm,
Antero Kukko,
Xinlian Liang,
Juha Hyyppä
Publication year - 2015
Publication title -
the photogrammetric journal of finland/the photogrammetric journal of finland
Language(s) - English
Resource type - Journals
eISSN - 1799-2486
pISSN - 0554-1069
DOI - 10.17690/015242.2
Subject(s) - backpack , laser scanning , outlier , computer science , artificial intelligence , computer vision , remote sensing , laser , geography , optics , physics , archaeology
Backpack mobile laser scanners provide rapid data acquisition and allow access to all walkable areas. We aim to remove outliers from the data of a prototype backpack mobile laser scanning system. After removing dark intensity points, our approach mainly uses voxel grids. Firstly, we remove points that only have a few points in the neighborhood. Secondly, we search for outlier clusters with a 3D convolution of voxel grids. Thirdly, outlier clusters located in the air or below the ground are removed with a single elimination bin. As a result, the majority of outliers are successfully removed from backpack mobile laser scanning data.
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