@article{ref1,
title="Pedestrian detection and tracking with night vision",
journal="IEEE transactions on intelligent transportation systems",
year="2005",
author="Xu, Fengliang and Liu, Xia and Fujimura, Kikuo",
volume="6",
number="1",
pages="63-71",
abstract="This paper presents a method for pedestrian detection and tracking using a single night-vision video camera installed on the vehicle. To deal with the nonrigid nature of human appearance on the road, a two-step detection/tracking method is proposed. The detection phase is performed by a support vector machine (SVM) with size-normalized pedestrian candidates and the tracking phase is a combination of Kalman filter prediction and mean shift tracking. The detection phase is further strengthened by information obtained by a road-detection module that provides key information for pedestrian validation. Experimental comparisons (e.g., grayscale SVM recognition versus binary SVM recognition and entire-body detection versus upper-body detection) have been carried out to illustrate the feasibility of our approach.<p />",
language="",
issn="1524-9050",
doi="10.1109/TITS.2004.838222",
url="http://dx.doi.org/10.1109/TITS.2004.838222"
}