Title :
Robust obstacle detection with monocular vision based on motion analysis
Author :
Demonceaux, C. ; Kachi-Akkouche, D.
Author_Institution :
CREA, Amiens, France
Abstract :
This paper deals with the problem of obstacle detection from a single camera mounted on a vehicle. We define an obstacle as any object that obstructs the vehicle´s driving path. The perception of the environment is performed through a fast processing of image sequence. The approach is based on motion analysis. Generally, the optical flow techniques are huge in computation time and sensitive to vehicle motion. To overcome these problems, we choose to detect the obstacle in two steps. The road motion is firstly computed through a fast and robust wavelets analysis. Then, we detect the areas which have a different motion thanks to a Bayesian modelization. Results shown in the paper prove that the proposed method permits the detection of any obstacle on a road.
Keywords :
Bayes methods; Markov processes; computer vision; image segmentation; image sequences; motion compensation; motion estimation; object detection; road vehicles; roads; wavelet transforms; Bayesian modelization; camera; image processing; image sequence; monocular vision; motion analysis; obstacle detection; optical flow techniques; road motion; robust obstacle detection; vehicle driving path; vehicle motion; wavelets analysis; Cameras; Image motion analysis; Image sequences; Motion analysis; Motion detection; Optical sensors; Roads; Robustness; Vehicle detection; Vehicle driving;
Conference_Titel :
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN :
0-7803-8310-9
DOI :
10.1109/IVS.2004.1336439