Memorias de investigación
Ponencias en congresos:
Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework
Año:2011
Áreas de investigación
  • Procesado y análisis de la señal
Datos
Descripción
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
Internacional
Si
Nombre congreso
IEEE Conf. on Intelligent Transportation Systems, ITSC 2011
Tipo de participación
960
Lugar del congreso
Washington D. C.
Revisores
Si
ISBN o ISSN
2153-0009
DOI
10.1109/ITSC.2011.6082905
Fecha inicio congreso
05/10/2011
Fecha fin congreso
07/10/2012
Desde la página
1942
Hasta la página
1947
Título de las actas
Proc. ITSC'11
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Javier Marinas Mateos UPM
  • Autor: Luis Salgado Alvarez de Sotomayor UPM
  • Autor: Jon Arróspide Laborda UPM
  • Autor: Marcos Nieto Vicomtech-IK4, Research Alliance
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones