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.
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