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This paper studies the node-selection problem for target localization in wireless camera sensor networks. The goal of node selection is to optimize the tradeoff between the energy consumption of wireless camera sensor networks and the quality of target localization. We propose a cooperative target localization algorithm, which is implemented by two phases: 1) target detecting phase and 2) target locating phase. For the target detecting phase, we develop a probing environment and adaptive sleeping (PEAS)-based density control algorithm to select the proper subset of deployed camera sensors for maintaining the desired density of nodes in the detecting mode. For the locating phase, we map the node-selection problem into an optimization problem and then propose an optimal node-selection algorithm to select a subset of camera sensors for estimating the location of a target while minimizing the energy cost. We conduct extensive experiments and simulations to validate and evaluate our proposed schemes.