Abstract In this paper, we present our approach to robust background modelling which combines visible and thermal infrared spectrum data. Our work is based on the non-parametric background model describe in 1. We use a pedestrian detection module to prevent erroneous data from becoming part of the background model and this allows us to initialise our bacjground model, even in the presence of foreground objects. Visible and infrared features are use to remove incorrectly detected foreground regions. Allowing our model to quickly recover from ghost regions and rapid lighting changes. An object-based shadow detector also improves our algorithm's performance.

Url http://doras.dcu.ie/240/1/ieee_iccvpr_2005.pdf

Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Digital Video Processing (CDVP)
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Adaptive Information Cluster (AIC)
Ireland -> Dublin City University -> Subject = Computer Science: Digital video
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres