  This paper investigates cooperative estimation of 3D target object motion for
visual sensor networks. In particular, we consider the situation where multiple
smart vision cameras see a group of target objects. The objective here is to
meet two requirements simultaneously: averaging for static objects and tracking
to moving target objects. For this purpose, we present a cooperative estimation
mechanism called networked visual motion observer. We then derive an upper
bound of the ultimate error between the actual average and the estimates
produced by the present networked estimation mechanism. Moreover, we also
analyze the tracking performance of the estimates to moving target objects.
Finally the effectiveness of the networked visual motion observer is
demonstrated through simulation.
