Advanced Correlation Tracking of Objects in Cluttered Imagery

Correlation tracking is used in civilian and military automatic target recognition and surveillance systems, to track objects based on their 2-dimensional shape. However traditional correlation-tracking systems have difficulty robustly detecting an object when the object is partially obscured by clutter. This paper describes one of the main problems of image-based correlation tracking systems, and proposes a novel solution. The reference image update problem occurs when the tracked object undergoes rapid shape change in the presence of clutter, here the reference image of the target is updated with an image corrupted by clutter, this can cause the system to walk-off and lose track of the target-object. The novel solution presented is based on research into modelling biological vision systems. We developed a prototype system designed to track an object changing size and shape in the presence of obscuring clutter. The system was tested on both real and simulated infrared imagery of aircraft found to be robust in the presence of obscuring clutter.