Object tracking in a varying environment

This paper describes the tracking of an object in a sequence of video-recorded images by a template matching approach based on a genetic algorithm learning technique to generate adaptive templates. The system is intended for real images. Contrary to a controlled environment, where the template may be generated from a noise free image and all successive frames do not show great changes, we hypothesise a set of images acquired at possible different environmental conditions. The varying environmental conditions greatly influence the matching, but they cannot be coded/used because they are not known a priori. In addition, 2D projections of 3D objects may vary during the sequence. Despite these difficulties, the need for robust systems that can locate objects in frame sequences is rapidly increasing due to the explosion in the amount of visual data in the communications systems