In this paper we present a pipeline for automatic detection of traffic signs in images. The proposed system can deal with high appearance variations, which typically occur in traffic sign recognition applications, especially with strong illumination changes and dramatic scale changes. Unlike most existing systems, our pipeline is based on interest regions extraction rather than a sliding window detection scheme. The proposed approach has been specialized and tested in three variants, each aimed at detecting one of the three categories of Mandatory, Prohibitory and Danger traffic signs. Our proposal has been evaluated experimentally within the German Traffic Sign Detection Benchmark competition.
A traffic sign detection pipeline based on interest region extraction / Samuele Salti; Alioscia Petrelli; Federico Tombari; Nicola Fioraio; Luigi Di Stefano. - STAMPA. - (2013), pp. 1-7. (Intervento presentato al convegno Neural Networks (IJCNN), The 2013 International Joint Conference on tenutosi a Dallas, TX - USA nel 4-9 Aug. 2013) [10.1109/IJCNN.2013.6706808].
A traffic sign detection pipeline based on interest region extraction
SALTI, SAMUELE;PETRELLI, ALIOSCIA;TOMBARI, FEDERICO;FIORAIO, NICOLA;DI STEFANO, LUIGI
2013
Abstract
In this paper we present a pipeline for automatic detection of traffic signs in images. The proposed system can deal with high appearance variations, which typically occur in traffic sign recognition applications, especially with strong illumination changes and dramatic scale changes. Unlike most existing systems, our pipeline is based on interest regions extraction rather than a sliding window detection scheme. The proposed approach has been specialized and tested in three variants, each aimed at detecting one of the three categories of Mandatory, Prohibitory and Danger traffic signs. Our proposal has been evaluated experimentally within the German Traffic Sign Detection Benchmark competition.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
