Object tracking through adaptive correlation

Abstract

Current Air Force interests include a desire to track an object based on its shape once it has been designated as a target. The use of a correlation-based system to track an object through a series of images based on templates derived from previous image frames is discussed. The ability to track is extended to sequences that include multiple objects of interest within the field of view. This is accomplished by comparing the height and shape of the template autocorrelation to the peaks in the correlation of the template with the next scene. The result is to identify the region in the next scene that best matches the designated target. In addition to correlation plane postprocessing, an adaptive window is used to determine the template size to reduce the effects of correlator walkoff. The image sequences used were taken from a forward-looking infrared sensor mounted on board a DC-3 aircraft. The images contain a T-55 tank and both an M-113 and a TAB-71 armored personnel carrier moving in a columnized formation along a dirt road. This research presents techniques to (1) track targets in the presence of other, and sometimes brighter, targets of similar shape, (2) to maintain small tracking errors, and (3) to reduce the effects of correlator walk-off.