%0 Conference Proceedings
%T Pedestrian Candidates Generation using Monocular Cues
%A Diego Cheda
%A Daniel Ponsa
%A Antonio Lopez
%B IEEE Intelligent Vehicles Symposium
%D 2012
%I IEEE Xplore
%@ 1931-0587
%@ 978-1-4673-2119-8
%F Diego Cheda2012
%O ADAS
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2013), last updated on Sun, 22 May 2016 19:43:50 +0200
%X Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached.
%K pedestrian detection
%U http://refbase.cvc.uab.es/files/cpl2012d.pdf
%U http://dx.doi.org/10.1109/IVS.2012.6232117
%P 7-12