Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
This paper presents an automatic efficient method to fit a statistical deformation model of the human face to 3D scan data. In a global to local fitting scheme, the shape parameter...
We present a new method of fitting an element-free volumetric model to a sequence of deforming surfaces of a moving object. Given a sequence of visual hulls, we iteratively fit an...
Jaeil Choi, Andrzej Szymczak, Greg Turk, Irfan A. ...
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...