Vehicle detection based on distributed sensor decision fusion

被引：0

作者：

Li, B ^{[1
]}

Wang, RB ^{[1
]}

Guo, KY ^{[1
]}

机构：

[1] Jilin Univ, Intelligent Vehicle Res Grp, Changchun, Peoples R China

来源：

IEEE 5TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, PROCEEDINGS | 2002年

关键词：

fuzzy a priori probability and cost; minimum Bayesian risk; sensor fusion; vehicle detection;

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：

Obstacle detection is one of the key functions to intelligent vehicle (IV). In this paper, the recent work of IV research group of Jilin University (JLU) of China in detecting the preceding vehicle is introduced. Firstly, A brief overview is given of the vehicle detection approach based on CCD camera and laser radar respectively. Then a new vehicle detection method based on distributed bi-sensor decision fusion is put forward. On the basis of minimum Bayesian risk criterion and fuzzy a priori probability and fuzzy cost function, the binary decision fusion rule is established. Experiment results are also presented.

引用

页码：242 / 247

页数：6