This paper proposes an improvement of Advanced Driver Assistance System based on saliency estimation of road signs. After a road sign detection stage, its saliency is estimated using a SVM learning. A model of visual saliency linking the size of an object and a size-independent saliency is proposed. An eye tracking experiment in context close to driving proves that this computational evaluation of the saliency fits well with human perception, and demonstrates the applicability of the proposed estimator for improved ADAS.
Alerting the drivers about road signs with poor visual saliency
01.06.2009
1663790 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Alerting the Drivers about Road Signs with Poor Visual Saliency
British Library Conference Proceedings | 2009
|Saliency assistant driver alerting
IEEE | 2013
|Drivers' understanding of road traffic signs
Engineering Index Backfile | 1964
|