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Author (up) Alex Ferrin; Julio Larrea; Miguel Realpe; Daniel Ochoa
Title Detection of utility poles from noisy Point Cloud Data in Urban environments. Type Conference Article
Year 2018 Publication Artificial Intelligence and Cloud Computing Conference (AICCC 2018) Abbreviated Journal
Volume Issue Pages 53-57
Abstract In recent years 3D urban maps have become more common, thus providing complex point clouds that include diverse urban furniture such as pole-like objects. Utility poles detection in urban environment is of particular interest for electric utility companies in order to maintain an updated inventory for better planning and management. The present study develops an automatic method for the detection of utility poles from noisy point cloud data of Guayaquil – Ecuador, where many poles are located next to buildings, or houses are built until the border of the sidewalk getting very close to poles, which increases the difficulty of discriminating poles, walls, columns, fences and building corners.
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Call Number gtsi @ user @ Serial 94
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