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.
GilbertBowdenECCV06.pdf - Accepted Version
Available under License : See the attached licence file.
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)|
|Additional Information:||The original publication is available at: http://www.springerlink.com|
|Uncontrolled Keywords:||VISUAL SURVEILLANCE|
|Divisions:||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Depositing User:||Symplectic Elements|
|Date Deposited:||11 Jun 2012 14:07|
|Last Modified:||23 Sep 2013 19:24|
Actions (login required)
Downloads per month over past year