Visibility analysis is an important application
of 3D GIS data. Current approaches require 3D city models that are often
derived from detailed aerial point clouds. We present an approach to
visibility analysis that does not require a city model but works directly
on the point cloud. Our approach is based on the medial axis transform,
which models the urban environment as a union of balls, which we then use
to construct a depthmap that is used for point visibility queries. As we
demonstrate through our experiments on a real-world aerial LiDAR point
cloud, the main benefits of our approach are 1) it is robust to noise,
irregular sampling and holes of typical aerial LiDAR datasets, 2) it gives
visibility results that are significantly more accurate than the often
highly generalised city models, and 3) it is a simple algorithm that is
easy to parallelise.
Categories and Subject Descriptors (according to ACM CCS): I.3.7
[Computer Graphics]: Picture/Image Generation-Visible line/surface
algorithms I.3.5 [Computer Graphics]: Computational Geometry and Object
Modeling
full paper
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