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The Peopleremover—Removing Dynamic Objects From 3-D Point Cloud Data by Traversing a Voxel Occupancy Grid | IEEE Journals & Magazine | IEEE Xplore

The Peopleremover—Removing Dynamic Objects From 3-D Point Cloud Data by Traversing a Voxel Occupancy Grid


Abstract:

Even though it would be desirable for most postprocessing purposes to obtain a point cloud without moving objects in it, it is often impractical or downright impossible t...Show More

Abstract:

Even though it would be desirable for most postprocessing purposes to obtain a point cloud without moving objects in it, it is often impractical or downright impossible to free a scene from all nonstatic clutter. Outdoor environments contain pedestrians, bicycles, and motor vehicles which cannot easily be stopped from entering the sensor range and indoor environments like factory production lines cannot be evacuated due to production losses during the time of the scan. In this letter, we present a solution to this problem that we call the “peopleremover.” Given a registered set of 3-D point clouds, we build a regular voxel occupancy grid and then traverse it along the lines of sight between the sensor and the measured points to find the differences in volumetric occupancy between the scans. Our approach works for scan slices from mobile mapping as well as for the more general scenario of terrestrial scan data. The result is a clean point cloud free of dynamic objects.
Published in: IEEE Robotics and Automation Letters ( Volume: 3, Issue: 3, July 2018)
Page(s): 1679 - 1686
Date of Publication: 05 February 2018

ISSN Information:


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