Real-time vehicle and lane detection with embedded hardware

被引：0

作者：

Kaszubiak, J ^{[1
]}

Tornow, M ^{[1
]}

Kuhn, RW ^{[1
]}

Michaelis, B ^{[1
]}

Knoeppel, C ^{[1
]}

机构：

[1] Univ Magdeburg, Inst Elect Signal Proc & Commun, D-39106 Magdeburg, Germany

来源：

2005 IEEE INTELLIGENT VEHICLES SYMPOSIUM PROCEEDINGS | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

For autonomously acting robots and driver assistance systems powerful optical stereo sensor systems are required. Object positions and environmental conditions have to be acquired in real-time. In this paper an algorithm based on a hardware-software co-design is applied. A depth-map is generated with a hierarchical detection method. A depthhistogram is generated by using the density distribution of the disparity in the depth-map. It is used for object detection. The object clustering can be accomplished without calculation of 3-d-points, due to the almost identical mapping of the objects over the whole distance, within the histogram. A lane detection is applied by using a Hough Transform. The suitability at night and the detection of small objects like bikers is proven.

引用

页码：619 / 624

页数：6

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