Target tracking in infrared imagery using weighted composite reference function-based decision fusion.

In this paper, we propose a novel decision fusion algorithm for target tracking in forward-looking infrared image sequences recorded from an airborne platform. An important part of this study is identifying the failure modes in this type of imagery. Our strategy is to prevent these failure modes from developing into tracking failures. The results furnished by competing ego-motion compensation and tracking algorithms are evaluated based on their similarity to a target model constructed using the weighted composite reference function.