Abstract This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated, non-overlapping cameras. Unlike other approaches this technique uses an incremental learning method, to model both the colour variations and posterior probability distributions of spatio-temporal links between cameras. These operate in parallel and are then used with an appearance model of the object to track across spatially separated cameras. The approach requires no pre-calibration or batch preprocessing, is completely unsupervised, and becomes more accurate over time as evidence is accumulated.
Tracking Objects Across Cameras by Incrementally Learning Inter-camera Colour Calibration and Patterns of Activity
Computer Vision – ECCV 2006 ; 3 ; 125-136
Lecture Notes in Computer Science ; 3952 , 3
2006-01-01
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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