Vision-Based Method for Forward Vehicle Detection and Tracking

被引：6
|
作者：
Li, Xing [1 ]
Guo, Xiaosong [1 ]
机构：
[1] Hightech Inst Xian, Xian, Peoples R China
来源：
2013 INTERNATIONAL CONFERENCE ON MECHANICAL AND AUTOMATION ENGINEERING (MAEE 2013) | 2013年
关键词：
Histogram of gradient; Support vector machine; Vehicle classifier; Forward vehicle detection and tracking; Kalman filter; Advanced driver assistance system;
D O I：
10.1109/MAEE.2013.41
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Vehicle detection and tracking is the basis of advanced driver assistance system. This paper focused on improving the performance of vehicle detection system with single camera and proposed a vision-based method for forward vehicle detection and tracking. The shadow underneath vehicle was segmented accurately by using histogram analysis method and utilized to detect vehicle at daytime. The initial candidates were generated by combining horizontal and vertical edge feature of shadow, and these initial candidates were further verified by using a vehicle classifier based on the histogram of gradient and support vector machine. Kalman filters were used for tracking of the detected vehicles to improve system performance. The results show that the proposed method could be adapt to different illumination circumstances robustly and has a detection rate of 95.78 percent and a false rate of 1.97 percent in normal light condition
引用
收藏
页码：128 / 131
页数：4
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