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Tracking objects across cameras by incrementally learning inter-camera colour calibration and patterns of activity

Gilbert, A and Bowden, R (2006) Tracking objects across cameras by incrementally learning inter-camera colour calibration and patterns of activity In: ECCV 2006, 2006-05-07 - 2006-05-13, Graz, Austria.

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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.

Item Type: Conference or Workshop Item (Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmail
Gilbert, AUNSPECIFIED
Bowden, RUNSPECIFIED
Date : 2006
Identification Number : 10.1007/11744047_10
Contributors :
ContributionNameEmail
EditorLeonardis, AUNSPECIFIED
EditorBischof, HUNSPECIFIED
EditorPinz, AUNSPECIFIED
PublisherSpringer, UNSPECIFIED
Uncontrolled Keywords : VISUAL SURVEILLANCE
Additional Information : The original publication is available at: http://www.springerlink.com
Depositing User : Symplectic Elements
Date Deposited : 11 Jun 2012 14:07
Last Modified : 23 Sep 2013 19:24
URI: http://epubs.surrey.ac.uk/id/eprint/531493

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