%0 Conference Proceedings
%T Adapting Pedestrian Detection from Synthetic to Far Infrared Images
%A Yainuvis Socarras
%A Sebastian Ramos
%A David Vazquez
%A Antonio Lopez
%A Theo Gevers
%B ICCV Workshop on Visual Domain Adaptation and Dataset Bias
%D 2013
%C Sydney, Australy
%G English
%F Yainuvis Socarras2013
%O ADAS; 600.054; 600.055; 600.057; 601.217;ISE
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2334), last updated on Thu, 10 Nov 2016 12:25:44 +0100
%X We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes.
%K Domain Adaptation
%K Far Infrared
%K Pedestrian Detection
%U http://refbase.cvc.uab.es/files/srv2013.pdf