DocumentCode :
2516325
Title :
On-road position estimation by probabilistic integration of visual cues
Author :
Popescu, Voichita ; Danescu, Radu ; Nedevschi, Sergiu
Author_Institution :
Comput. Sci. Dept., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear :
2012
fDate :
3-7 June 2012
Firstpage :
583
Lastpage :
589
Abstract :
This paper addresses the problem of finding the host vehicle´s lateral position on a multi-lane road, using information obtained by processing video sequences. A very important cue for lane identification is the class of the boundaries of the current lane. This paper presents a reliable solution for lane boundary type identification, based on frequency analysis of the gray level profile of these boundaries, assuming that the current lane is already detected. The lane boundary information is combined with the obstacle information, through a Bayesian Network which will output, frame by frame, the probability of the vehicle to be positioned on each lane of the road. The probability result will be propagated throughout the sequence by a Particle Filter.
Keywords :
Bayes methods; image sequences; object detection; particle filtering (numerical methods); road traffic; traffic engineering computing; video signal processing; Bayesian network; frequency analysis; gray level profile; lane boundary type identification; multilane road; obstacle information; on-road position estimation; particle filter; probabilistic integration; vehicle lateral position; video sequences; visual cues; Asphalt; Estimation; Filtering; Gray-scale; Roads; Vehicles; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2012 IEEE
Conference_Location :
Alcala de Henares
ISSN :
1931-0587
Print_ISBN :
978-1-4673-2119-8
Type :
conf
DOI :
10.1109/IVS.2012.6232182
Filename :
6232182
Link To Document :
بازگشت