This paper presents a new method for constructing compact statistical point-based models of ensembles of similar shapes that does not rely on any specific surface parameterization....
Joshua E. Cates, P. Thomas Fletcher, Martin Andrea...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
A new approach is presented for partitioning an image database by classifying and indexing the convex hull shapes and the number of region concavities. The result is a significant...
We describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. By combining a deformation-based method for mea...
Gustavo K. Rohde, Wei Wang, Tao Peng, Robert F. Mu...