%0 Journal Article 
%A Álvarez, S.
%A Sotelo Vázquez, Miguel Ángel
%A Ocaña Miguel, Manuel
%A Fernández Llorca, David
%A Parra Alonso, Ignacio
%A Bergasa Pascual, Luis Miguel
%T Perception advances in outdoor vehicle detection for automatic cruise control
%D 2010
%@ 0263-5747
%U http://hdl.handle.net/10017/45887
%X This paper describes a vehicle detection system based
on support vector machine (SVM) and monocular vision.
The final goal is to provide vehicle-to-vehicle time gap
for automatic cruise control (ACC) applications in the
framework of intelligent transportation systems (ITS). The
challenge is to use a single camera as input, in order to
achieve a low cost final system that meets the requirements
needed to undertake serial production in automotive industry.
The basic feature of the detected objects are first located in
the image using vision and then combined with a SVMbased classifier. An intelligent learning approach is proposed
in order to better deal with objects variability, illumination
conditions, partial occlusions and rotations. A large database
containing thousands of object examples extracted from real
road scenes has been created for learning purposes. The
classifier is trained using SVM in order to be able to classify
vehicles, including trucks. In addition, the vehicle detection
system described in this paper provides early detection of
passing cars and assigns lane to target vehicles. In the paper,
we present and discuss the results achieved up to date in real
traffic conditions.
%K Vision
%K Vehicle detection
%K Automatic cruise control
%K SVM (Support Vector Machine)
%K Intelligent transportation systems
%K Electrónica
%K Electronics
%~ Biblioteca Universidad de Alcala