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This paper describes a method of tracking multiple persons with occlusions using stereo. We previously developed an accurate and stable tracking method using overlapping silhouette templates which considers how persons overlap in the image. It realized a fast tracking by using an approximated likelihood map based on kernel density estimation. The method, however, treated only two overlapping persons...
This paper considers the problem of bearings only tracking of manoeuvring targets. A learning particle filtering algorithm is proposed which can estimate both the unknown target states and unknown model parameters. The algorithm performance is validated and tested over a challenging scenario with abrupt manoeuvres. A comparison of the proposed algorithm with the Interacting Multiple Model (IMM) filter...
This paper describes a method of tracking multiple persons with occlusions using stereo. Many previous stereo-based systems track each person separately and do not explicitly handle such occlusions. We previously developed an accurate, stable tracking method using overlapping silhouette templates which considers how persons overlap in the image. However, because the method uses a particle filter,...
This paper presents algorithms for consistent joint localisation and tracking of multiple targets in wireless sensor networks under the decentralised data fusion (DDF) paradigm where particle representations of the state posteriors are communicated. This work differs from previous work as more generalised methods have been developed to account for correlated estimation errors that arise due to common...
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