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Vision-based Pedestrian Protection Systems for Intelligent Vehicles (Paperback, 2014 ed.)
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Vision-based Pedestrian Protection Systems for Intelligent Vehicles (Paperback, 2014 ed.)
Series: SpringerBriefs in Computer Science
Expected to ship within 10 - 15 working days
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Pedestrian Protection Systems (PPSs) are on-board systems aimed at
detecting and tracking people in the surroundings of a vehicle in
order to avoid potentially dangerous situations. These systems,
together with other Advanced Driver Assistance Systems (ADAS) such
as lane departure warning or adaptive cruise control, are one of
the most promising ways to improve traffic safety. By the use of
computer vision, cameras working either in the visible or infra-red
spectra have been demonstrated as a reliable sensor to perform this
task. Nevertheless, the variability of human's appearance, not only
in terms of clothing and sizes but also as a result of their
dynamic shape, makes pedestrians one of the most complex classes
even for computer vision. Moreover, the unstructured changing and
unpredictable environment in which such on-board systems must work
makes detection a difficult task to be carried out with the
demanded robustness. In this brief, the state of the art in PPSs is
introduced through the review of the most relevant papers of the
last decade. A common computational architecture is presented as a
framework to organize each method according to its main
contribution. More than 300 papers are referenced, most of them
addressing pedestrian detection and others corresponding to the
descriptors (features), pedestrian models, and learning machines
used. In addition, an overview of topics such as real-time aspects,
systems benchmarking and future challenges of this research area
are presented.
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