—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Recently, nonrigid shape matching has received more and more attention. For nonrigid shapes, most neighboring points cannot move independently under deformation due to physical co...
—This paper develops a framework for locally deforming either a parametric surface or hierarchical subdivision surface to match a set of positional and energy minimizing constrai...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...