@article{ref1,
title="Pedestrian Detection and Tracking in an Urban Environment Using a Multilayer Laser Scanner",
journal="IEEE transactions on intelligent transportation systems",
year="2010",
author="Gidel, S. and Checchin, P. and Blanc, C. and Chateau, T. and Trassoudaine, L.",
volume="11",
number="3",
pages="579-588",
abstract="Pedestrians are the most vulnerable participants in urban traffic. The first step toward protecting pedestrians is to reliably detect them in a real-time framework. In this paper, a new approach is presented for pedestrian detection in urban traffic conditions using a multilayer laser sensor mounted onboard a vehicle. This sensor, which is placed on the front of a vehicle, collects information about the distance distributed according to four planes. Like a vehicle, a pedestrian constitutes, in the vehicle environment, an obstacle that must be detected, and located and then identified and tracked if necessary. To improve the robustness of pedestrian detection using a single laser sensor, a detection system based on the fusion of information located in the four laser planes is proposed. The method uses a nonparametric kernel-density-based estimation of pedestrian position of each laser plane. The resulting pedestrian estimations are then sent to a decentralized fusion according to the four planes. Temporal filtering of each object is finally achieved within a stochastic recursive Bayesian framework (particle filter), allowing a closer observation of pedestrian random movement dynamics. Many experimental results are given and validate the relevance of our pedestrian-detection algorithm with regard to a method using only a single-row laser-range scanner.<p />",
language="",
issn="1524-9050",
doi="10.1109/TITS.2010.2045122",
url="http://dx.doi.org/10.1109/TITS.2010.2045122"
}