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

页码：2073 / +

页数：2

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