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Removing non-static objects from 3D laser scan data
ISPRS Journal of Photogrammetry and Remote Sensing (JPRS), (2018)
DOI: 10.1016/j.isprsjprs.2018.05.019
Аннотация
For the purpose of visualization and further
post-processing of 3D point cloud data, it is often
desirable to remove moving objects from a given data
set. Common examples for these moving objects are
pedestrians, bicycles and motor vehicles in outdoor
scans or manufactured goods and employees in indoor
scans of factories. We present a new change
detection method which is able to partition the
points of multiple registered 3D scans into two
sets: points belonging to stationary (static)
objects and points belonging to moving (dynamic)
objects. Our approach does not require any object
detection or tracking the movement of objects over
time. Instead, we traverse a voxel grid to find
differences in volumetric occupancy for “explicit”
change detection. Our main contribution is the
introduction of the concept of “point shadows” and
how to efficiently compute them. Without them, using
voxel grids for explicit change detection is known
to suffer from a high number of false positives when
applied to terrestrial scan data. Our solution
achieves similar quantitative results in terms of
F1-score as competing methods while at the same time
being faster.
