@InProceedings{VictorBorjas2013,
author="Victor Borjas
and Jordi Vitria
and Petia Radeva",
title="Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments",
booktitle="13th IAPR Conference on Machine Vision Applications",
year="2013",
abstract="Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87\% of the false positives and therefore the overall precision of the detectionwas increased signicantly.",
optnote="OR; MILAB;MV",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2238), last updated on Thu, 10 Nov 2016 11:56:13 +0100",
file=":http://refbase.cvc.uab.es/files/BVR2013.pdf:PDF"
}