The goal of this communication is to present a weighted likelihood discriminant for minimum error shape classification. Different from traditional Maximum Likelihood (ML) methods...
Detection, tracking, segmentation and pose estimation of people in monocular images are widely studied. Two-dimensional models of the human body are extensively used, however, they...
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
Within the field of pattern classification, the Fisher kernel is a powerful framework which combines the strengths of generative and discriminative approaches. The idea is to ch...
We focus on credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. We replace the notion of strong independence commonly used in credal ne...
Gert de Cooman, Filip Hermans, Alessandro Antonucc...