Adaptive window algorithm with four-direction sizing factors for robust correlation-based tracking

Abstract

The authors propose the adaptive window algorithm with four-direction sizing factors (AWA-FSF) for robust correlation-based tracking in complex cluttered environments. When the size and shape of a moving object have been changed, the correlator often accumulates walk-off error. The success of correlation-based tracking largely depends on choosing a suitable window size and position and thus transferring the proper reference image to the next frame. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, one can minimize the influence of complex background and clutter. In addition, one can finely tune the center point of the reference image repeatedly after the main tracking process. Thus one has increased stability and reliability of correlation-based image tracking. They tested the performance of the AWA-FSF using 45 real image sequences made of over 3400 images.