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To track 3-dimensional multiple visual-targets states, the authors develop the decentralized Wireless Camera Sensor Network (WCSN) and the corresponding data fusion scheme. In their proposed scheme, each activated camera sensor-node obtains the local encoded 2-dimensional observation of the visual-targets' states and sends it to the global fusion center. This global fusion center processes the local information and provide the 3- dimensional estimation of the multiple visual-target states. They also propose the distributed visual-PHD (Probability Hypothesis Density) filtering algorithm which can be used to detect the mobile visual-targets' random appearance and disappearance in the clutter environments with high accuracy and low computational complexity.
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