Tracking of multiple objects in the presence of occlusion in moderately complex scenes. Most conventional tracking algorithms work well when only one object is tracked at a time. We introduce a real-time solution to this problem by using a probabilistic mixing of low-level features and components. The algorithm mixes motion estimates, change detection information and unobservable predictions to create accurate trajectories of moving objects.