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Particle impoverishment, which always leads to accuracy decreasing, is a classical problem of the traditional particle filter resampling. A particle filter resampling method based on improved genetic algorithm is proposed in this paper to solve the problem. In the improved algorithm, a genetic resampling step is applied for particle reproduction. The main work of the improved algorithm include two...
We propose a Bayesian tracking algorithm based on adaptive fragmentation and variational approximation. By using the cue of gradient, we fragment the target into disconnected rectangles and reduce the confusion from the background. To handle the uncertainties in real tracking case, we choose the Bayesian framework with a variational implementation. The parameters of the variational inference are updated...
A hybrid signal processing scheme is proposed for distributed multi-target tracking (MTT). For the sake of resource efficiency in a wireless sensor network (WSN), we reduce the problem to parallel cluster-based single target tracking when the targets are far apart, and switch to MTT only when data association becomes ambiguous. A sequential monte carlo method is employed to assign the ambiguous observations...
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