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This paper presents a vision-based system for cooperative object detection, localization and tracking using Wireless Sensor Networks (WSNs). The proposed system exploits the distributed sensing capabilities, communication infrastructure and parallel computing capabilities of the WSN. To reduce the bandwidth requirements, the images captured are processed at each camera node with the objective of extracting the location of the object on each image plane, which is transmitted to the WSN. The measures from all the camera nodes are processed by means of sensor fusion techniques such as Maximum Likelihood (ML) and Extended Kalman Filter (EKF). The paper describes hardware and software aspects and presents some experimental results.
Sánchez-Matamoros et al. (Thu,) studied this question.