Bayesian Assembly of 3D Axially Symmetric Shapes from Fragments

We present a complete system for the purpose of automatically assembling 3D pots given 3D measurements of their fragments commonly called sherds. A Bayesian approach is formulated which, at present, models the data given a set of sherd geometric parameters. Dense sherd measurement data is obtained by scanning the outside surface of each sherd with a laser scanner. Mathematical models, specified by a set of geometric parameters, represent the sherd outer surface and break curves on the outer surface (where two sherds have broken apart). Optimal alignment of assemblies of sherds, called configurations, is implemented as maximum likelihood estimation (MLE) of the surface and break curve parameters given the measured sherd data for all sherds in a configuration. The assembly process starts with a fast clustering scheme which approximates the MLE solution for all sherd pairs, i.e., configurations of size 2, using a subspace of the geometric parameters, i.e., the sherd break curves. More ac...

• Type: Conference
• Year: 2004
• Where: CVPR
• Authors: Andrew R. Willis, David B. Cooper
• Keywords: Accurate Mle Values, Break Curve Parameters, Break Curves, Computer Vision, CVPR 2004, Geometric Parameters, Sherd Geometric Parameters