Accurate real-time tracking using mutual information

Abstract

In this paper we present a direct tracking approach that uses Mutual Information (MI) as a metric for alignment. The proposed approach is robust, real-time and gives an accurate estimation of the displacement that makes it adapted to augmented reality applications. MI is a measure of the quantity of information shared by signals that has been widely used in medical applications. Since then, and although MI has the ability to perform robust alignment with illumination changes, multi-modality and partial occlusions, few works propose MI-based applications related to object tracking in image sequences due to some optimization problems.