Abstract
Modern photogrammetric methods as well as laser
measurement systems make it easy to collect large 3D
point clouds that sample objects or
environments. Several mechanisms are available in
literature for storing and compressing point clouds,
e.g., applying conventional image based compression
methods to 3D point clouds. In this challenge entry
however, we make use of octree subsampling and
compression, which is nicely suited for
unstructured, registered 3D point clouds of
arbitrarily shaped objects.
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