Y. Cao and D. Mumford (USA)
Shape analysis, 3D data analysis, Surface of revolution, Symmetric axis
The recovery of geometric structure from noisy data poses difficult non-linear statistical estimation problems. This paper describes a novel, robust, low computational cost approach for finding the geometric structure of an axi ally symmetric pot from a small fragment of it (an unorga nized set of 3D points). This problem is of great archaeo logical importance to the study of the hundreds and thou sands of shards found at excavation sites. Our method is based on the following fact: for each point on the surface, the center of the sphere of principal curvature correspond ing to the circles of revolution is on the symmetric axis. By finding the line which minimizes the weighted least squares distance to the estimated centers, we can find first the symmetric axis and then the profile curve. Because of the special properties of a surface of revolution, we can do this using only first derivatives, hence this method is robust to noisy data. We then use bootstrap methods to find con fidence bounds for the axis and the profile curve. These confidence bounds are essential if the estimations are used for the assembly of the full pot from multiple sherds.
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