@InProceedings{SergioEscalera2009,
author="Sergio Escalera
and Xavier Baro
and Jordi Vitria
and Petia Radeva",
title="Text Detection in Urban Scenes (video sample)",
booktitle="12th International Conference of the Catalan Association for Artificial Intelligence",
year="2009",
volume="202",
pages="35--44",
abstract="Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches",
optnote="OR;MILAB;HuPBA;MV",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1181), last updated on Tue, 17 Dec 2013 13:19:35 +0100",
isbn="978-1-60750-061-2",
doi="10.3233/978-1-60750-061-2-35"
}