DocumentCode :
2903971
Title :
Visual state estimation of traffic lights using hidden Markov models
Author :
Nienhüser, Dennis ; Drescher, Markus ; Zöllner, J. Marius
Author_Institution :
Intell. Syst. & Production Eng., FZI Forschungszentrum Inf., Karlsruhe, Germany
fYear :
2010
fDate :
19-22 Sept. 2010
Firstpage :
1705
Lastpage :
1710
Abstract :
The comprehension of dynamic objects in the environment is a major concern of prospective assistance systems. Among the relevant dynamic objects are not only road users, but also parts of the traffic infrastructure: Traffic lights switch between different light colors to manage traffic at intersections. We propose a camera-based approach to incorporate the visual information of traffic lights. Assistance systems can use it to realize comfort, fuel economy and safety functions. We focus on the classification and state estimation using support vector machines and hidden Markov models. Our system is able to distinguish different types of traffic lights - even blinking lights - in real-time.
Keywords :
driver information systems; hidden Markov models; image colour analysis; image sensors; state estimation; support vector machines; camera-based approach; hidden Markov models; prospective assistance systems; support vector machines; traffic light visual state estimation; Cameras; Hidden Markov models; Histograms; Image color analysis; Pixel; State estimation; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2010 13th International IEEE Conference on
Conference_Location :
Funchal
ISSN :
2153-0009
Print_ISBN :
978-1-4244-7657-2
Type :
conf
DOI :
10.1109/ITSC.2010.5625241
Filename :
5625241
Link To Document :
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