Expectation Propagation for approximate Bayesian inference
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Nonparametric belief propagation for self-calibration in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Distributed tracking in a large-scale network of smart cameras
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
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We propose a fully distributed message passing algorithm based on expectation propagation for the purpose of sensor localization. Sensors perform noisy measurements of their mutual distances and their relative angles. These measurements form the basis for an iterative, local (i.e. distributed) algorithm to compute the sensor's locations including uncertainties for these estimates. This approach offers a distributed, computationally efficient and flexible framework for information fusion in sensor networks.