(Georgia Institute of Technology, 2004-05)
Kaess, Michael; Zboinski, Rafal; Dellaert, Frank
We investigate the automated reconstruction of piecewise
smooth 3D curves, using subdivision curves as a simple but flexible curve
representation. This representation allows tagging corners to model nonsmooth
features along otherwise smooth curves. We present a reversible
jump Markov chain Monte Carlo approach which obtains an approximate
posterior distribution over the number of control points and tags.
In a Rao-Blackwellization scheme, we integrate out the control point locations,
reducing the variance of the resulting sampler. We apply this
general methodology to the reconstruction of piecewise smooth curves
from multiple calibrated views, in which the object is segmented from the
background using a Markov random field approach. Results are shown
for multiple images of two pot shards as would be encountered in archaeological
applications.