Object tracking in a varying environment

An object tracking system based on a template matching approach is demonstrated. The system identifies the target and tracks a sequence of video-recorded images without losing the object by using a genetic algorithm (GA)-based learning to adapt template matching processes to environmental conditions. The adaptive GA generates templates better than fixed, random or indexed template generation techniques in terms of both the cross-correlation score and time necessary to choose the template model. While the overload using the GA is minimal if it is not necessary to change template model, in all other cases the GA offers a better solution to the search the associated search and optimization problem than usual algorithms.