@Article{MarcoPedersoli2014,
author="Marco Pedersoli
and Jordi Gonzalez
and Xu Hu
and Xavier Roca",
title="Toward Real-Time Pedestrian Detection Based on a Deformable Template Model",
journal="IEEE Transactions on Intelligent Transportation Systems",
year="2014",
volume="15",
number="1",
pages="355--364",
abstract="Most advanced driving assistance systems already include pedestrian detection systems. Unfortunately, there is still a tradeoff between precision and real time. For a reliable detection, excellent precision-recall such a tradeoff is needed to detect as many pedestrians as possible while, at the same time, avoiding too many false alarms; in addition, a very fast computation is needed for fast reactions to dangerous situations. Recently, novel approaches based on deformable templates have been proposed since these show a reasonable detection performance although they are computationally too expensive for real-time performance. In this paper, we present a system for pedestrian detection based on a hierarchical multiresolution part-based model. The proposed system is able to achieve state-of-the-art detection accuracy due to the local deformations of the parts while exhibiting a speedup of more than one order of magnitude due to a fast coarse-to-fine inference technique. Moreover, our system explicitly infers the level of resolution available so that the detection of small examples is feasible with a very reduced computational cost. We conclude this contribution by presenting how a graphics processing unit-optimized implementation of our proposed system is suitable for real-time pedestrian detection in terms of both accuracy and speed.",
optnote="ISE; 601.213; 600.078",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2350), last updated on Wed, 21 Jun 2017 12:48:47 +0200",
issn="1524-9050",
doi="10.1109/TITS.2013.2281207",
file=":http://refbase.cvc.uab.es/files/PGH2014.pdf:PDF"
}