Mode changing tracker for ground target tracking on aerial images from unmanned aerial vehicles (ICCAS 2013)

This paper addresses mode changing tracker that has global and local tracking mode for efficient target tracking in aerial images from unmanned aerial vehicle. There are two modes in this tracker; Global tracking for object detection and local object tracking. In global tracking, an object in current image sequence is detected with covariance matrix matching. The covariance matrix is one of the efficient ways describing models as fusion of spatial and statistical properties of features. In local tracking, tracker conducts object tracking with kernel-based object tracking algorithm. Kernel-based object tracking algorithm, also known as mean shift, is one of the modern object tracking approaches. We demonstrate the performance of the tracker on aerial image sequences.