Passivity-based cooperative estimation of 3D target motion for visual sensor networks: Analysis on averaging performance

This paper presents a novel cooperative estimation algorithm for visual sensor networks. We consider the situation where multiple smart vision cameras with computation and communication capability see a group of target objects. The objective of the present algorithm is to meet two requirements: averaging and tracking. In order to meet the requirements simultaneously, we present a cooperative estimation algorithm based on passivity of the kinematic model of rigid body motion. We then provide an upper bound of the ultimate error between the actual average and the estimates given by the present algorithm. Finally the effectiveness of the present estimation algorithm is demonstrated through experiments.