Validation of blind region learning and tracking

Multi view tracking systems enable an object's identity to be preserved as it moves through a wide area surveillance network of cameras. One limitation of these systems is an inability to track objects between blind regions, i.e. pans of the scene that are not observable by the network of cameras. Recent interest has been shown in blind region learning and tracking but not much work has been reported on the systematic performance evaluation of these algorithms. The main contribution of this paper is to define a set of novel techniques that can be employed to validate a camera topology model, and a blind region multi view tracking algorithm.