1 research outputs found
Skeleton Extraction from 3D Point Clouds by Decomposing the Object into Parts
Decomposing a point cloud into its components and extracting curve skeletons
from point clouds are two related problems. Decomposition of a shape into its
components is often obtained as a byproduct of skeleton extraction. In this
work, we propose to extract curve skeletons, from unorganized point clouds, by
decomposing the object into its parts, identifying part skeletons and then
linking these part skeletons together to obtain the complete skeleton. We
believe it is the most natural way to extract skeletons in the sense that this
would be the way a human would approach the problem. Our parts are generalized
cylinders (GCs). Since, the axis of a GC is an integral part of its definition,
the parts have natural skeletal representations. We use translational symmetry,
the fundamental property of GCs, to extract parts from point clouds. We
demonstrate how this method can handle a large variety of shapes. We compare
our method with state of the art methods and show how a part based approach can
deal with some of the limitations of other methods. We present an improved
version of an existing point set registration algorithm and demonstrate its
utility in extracting parts from point clouds. We also show how this method can
be used to extract skeletons from and identify parts of noisy point clouds. A
part based approach also provides a natural and intuitive interface for user
interaction. We demonstrate the ease with which mistakes, if any, can be fixed
with minimal user interaction with the help of a graphical user interface