Incremental, scalable tracking of objects inter camera

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Incremental, scalable tracking of objects inter camera
This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated cameras with non overlapping fields of view. The approach relies on the three cues of colour, relative size and movement between cameras to describe the relationship of objects between cameras. This relationship weights the observation likelihood for correlating or tracking objects between cameras. Any individual cue alone has poor performance, but when fused together, a large boost in accuracy is gained. Unlike previous work, this paper uses an incremental technique to learning. The three cues are learnt in parallel and then fused together to track objects across the spatially separated cameras. The colour appearance cue is incrementally calibrated through transformation matrices, while probabilistic links, modelling an object's bounding box, between cameras represent the objects relative size. Probabilistic region links between entry and exit areas on cameras prov...
Andrew Gilbert, Richard Bowden
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where CVIU
Authors Andrew Gilbert, Richard Bowden
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