TY - JOUR
T1 - Vision-based Road Detection Using Road Models
AU - Alvarez, Jose M.
AU - Gevers, Theo
AU - Lopez, Antonio M.
PY - 2009
Y1 - 2009
N2 - Vision-based road detection is very challenging since the road is in an outdoor scenario imaged from a mobile platform.In this paper, a new top-down road detection algorithm is proposed. The method is based on scene (road) classification which provides the probability that an image contains certain type of road geometry (straight, left/right curve, etc.). During the training of the classifier a road probability map is also learned for each road geometry. Then, the proper pixel-based method is selected and fused to provide an improved road detection approach.From experiments it is concluded that the proposed method outperforms state of the art algorithms in a frame by frame context.
AB - Vision-based road detection is very challenging since the road is in an outdoor scenario imaged from a mobile platform.In this paper, a new top-down road detection algorithm is proposed. The method is based on scene (road) classification which provides the probability that an image contains certain type of road geometry (straight, left/right curve, etc.). During the training of the classifier a road probability map is also learned for each road geometry. Then, the proper pixel-based method is selected and fused to provide an improved road detection approach.From experiments it is concluded that the proposed method outperforms state of the art algorithms in a frame by frame context.
KW - Road detection
KW - Scene classification
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=uab_pure&SrcAuth=WosAPI&KeyUT=WOS:000280464300513&DestLinkType=FullRecord&DestApp=WOS
U2 - 10.1109/ICIP.2009.5414321
DO - 10.1109/ICIP.2009.5414321
M3 - Article
SP - 2073
EP - 2076
JO - Ieee International Conference On Image Processing Icip
JF - Ieee International Conference On Image Processing Icip
ER -