VISION-BASED ROAD DETECTION USING ROAD MODELS

被引：28
|
作者：
Alvarez, Jose M. [1 ]
Gevers, Theo [2 ]
Lopez, Antonio M. [1 ]
机构：
[1] Autonomous Univ Barcelona, Comp Vis Ctr, E-08193 Barcelona, Spain
[2] Univ Amsterdam, Fac Sci, NL-1012 WX Amsterdam, Netherlands
来源：
2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6 | 2009年
关键词：
Road detection; scene classification;
D O I：
10.1109/ICIP.2009.5414321
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：2073 / +
页数：2
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