Memorias de investigación
Communications at congresses:
Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework
Year:2011
Research Areas
  • Processing and signal analysis
Information
Abstract
In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion
International
Si
Congress
IEEE Conf. on Intelligent Transportation Systems, ITSC 2011
960
Place
Washington D. C.
Reviewers
Si
ISBN/ISSN
2153-0009
10.1109/ITSC.2011.6082905
Start Date
05/10/2011
End Date
07/10/2012
From page
1942
To page
1947
Proc. ITSC'11
Participants
  • Autor: Javier Marinas Mateos UPM
  • Autor: Luis Salgado Alvarez de Sotomayor UPM
  • Autor: Jon Arróspide Laborda UPM
  • Autor: Marcos Nieto Vicomtech-IK4, Research Alliance
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones