A New Spherical Mixture Model for Head Detection in Depth Images
Denis Brazey, Bruno Portier · SIAM Journal on Imaging Sciences · 2014
In this paper, we propose a new spherical mixture model for head detection in depth images. The shape of objects is considered through the statistical distribution of points in three-dimensional space. We first introduce a new probability density function belonging to the family of elliptical distributions and designed to model points spread near a spherical surface. The unknown parameters of the mixture model based on this new density are estimated with the expectation-maximization algorithm. The properties of the proposed estimators are studied from both the theoretical and practical points of view. We show the effectiveness of the proposed method for the problem of head detection. Results are compared to those obtained with RANSAC based methods.