In this paper, we apply the auction-based theories in economics to camera networks. We develop a set of auction protocols to do camera active control (pan/tilt/zoom) intelligently. Unlike the economic auction, the bid price in our case is formulated to have a vector representation, such that when a camera is available to follow multiple objects, we consider the "willingness" of this camera to track a particular object. Most of the computation is decentralized by computing the bid price locally while the final decision is made by a virtual auctioneer based on all the available bids, which is analogous to a real auction in economics. Thus, we can take the advantages of distributed/centralized computation and avoid their pitfalls. The experimental results show that the proposed approach is effective and efficient for dynamically active control based on user defined performance metrics.