Gaussian mixture model - universal background model (GMMUBM) is a standard reference classifier in speaker verification. We have recently proposed a simplified model using vect...
Tomi Kinnunen, Juhani Saastamoinen, Ville Hautam&a...
Background subtraction is an essential processing component for many video applications. However, its development has largely been application driven and done in ad hoc manners. I...
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
— Background subtraction is a method commonly used to segment objects of interest in image sequences. By comparing new frames to a background model, regions of interest can be fo...