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ECCV
2002
Springer

Fusion of Multiple Tracking Algorithms for Robust People Tracking

10 years 29 days ago
Fusion of Multiple Tracking Algorithms for Robust People Tracking
This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment. The new tracking system contains three co-operating parts: i) an Active Shape Tracker using a PCA-generated model of pedestrian outline shapes, ii) a Region Tracker, featuring region splitting and merging for multiple hypothesis matching, and iii) a Head Detector to aid in the initialisation of tracks. Data from the three parts are fused together to select the best tracking hypotheses. The new method is validated using sequences from surveillance cameras in a underground station. It is demonstrated that robust realtime tracking of people can be achieved with the new tracking system using standard PC hardware. Keywords. Visual Surveillance, People Tracking, Data Fusion, PCA.
Nils T. Siebel, Stephen J. Maybank
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 2002
Where ECCV
Authors Nils T. Siebel, Stephen J. Maybank
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