Title :
Obstacle detection in a road scene based on motion analysis
Author :
Demonceaux, Cédric ; Potelle, Alexis ; Kachi-Akkouche, Djemâa
Author_Institution :
Labortoire Amienois de Mathematique Fondamentale et Applique, Amiens, France
Abstract :
This paper deals with the problem of obstacle detection in traffic applications. The proposed device allows a driver to receive the current road and vehicle environment information. The perception of the environment is performed through a fast processing of image sequences acquired from a single camera mounted on a vehicle. This approach is based on frame motion analysis. The road motion is first computed through a fast and robust wavelets analysis. Finally, we detect the areas that have a different motion thanks to a Bayesian modelization. Results shown in this paper prove that the proposed method permits the detection of any obstacle on all type of road in various image conditions.
Keywords :
Bayes methods; Markov processes; cameras; image sequences; motion estimation; probability; recursive estimation; road traffic; wavelet transforms; Bayesian modelization; Markov random field; frame motion analysis; image sequences; motion analysis; motion estimation; obstacle detection; road detection; road scene; road traffic; wavelet analysis; Cameras; Image motion analysis; Image sequences; Layout; Motion analysis; Motion detection; Road vehicles; Robustness; Vehicle driving; Wavelet analysis; 65; Markov random field; motion analysis; obstacle detection; road detection; wavelet analysis;
Journal_Title :
Vehicular Technology, IEEE Transactions on
DOI :
10.1109/TVT.2004.834881