Abstract. In this paper we propose a new distance metric for probability density functions (PDF). The main advantage of this metric is that unlike the popular Kullback-Liebler (KL)...
In this paper, we introduce a new method for tracking multiple objects. The method combines Kalman filtering and the Expectation Maximization (EM) algorithm in a novel way to dea...
Foreground segmentation is one of the most challenging problems in computer vision. In this paper, we propose a new algorithm for static camera foreground segmentation. It combine...
A variational Bayesian framework is employed in the paper for image segmentation using color clustering. A Gaussian mixture model is used to represent color distributions. Variati...