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:2019,28(11):188-194
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基于车载图像的目标车辆压线检测方法
(中国科学技术大学 信息科学与技术学院 自动化系, 合肥 230027)
Lane-Crossing Detection Method of Vehicles with In-Vehicle Image
(Department of Automation, School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China)
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投稿时间:2019-04-18    修订日期:2019-05-16
中文摘要: 车辆压线检测是智能交通系统的一个重要功能,为此提出一种基于车载图像的目标车辆压线检测方法.首先,利用合成数据方法构建一个类型丰富多样的压线检测数据集;然后,结合图像语义分割方法完成车辆检测和车道线检测并以分割图形式表示结果,再使用前后轮估计的方法获取车辆前后轮的位置;最后,通过车轮与车道线位置对比实现车辆压线判断.实验表明,结合图像语义分割模型后,所提方法的压线检测平均准确率达到88.7%,平均耗时35 ms,具备一定的实际应用价值.
Abstract:Lane-crossing detection of vehicles is an important part of intelligent transportation system. To tackle this issue, we proposed a lane-crossing detection method of vehicles with in-vehicle image. First, we use synthesizing-data method to build a rich and varied lane-crossing detection dataset. Then, we use image semantic segmentation to detect vehicle and lane lines, and then we estimate wheels positions of vehicle. Finally, we contrast wheels positions with lane lines positions to judge whether there is lane-crossing behavior. Experiment results show that combined with semantic segmentation model, we achieve an average precision of 88.7% for lane-crossing detection, and the average detection time is 35 ms, which means that the proposed method has certain practical application value.
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基金项目:国家自然科学基金(61673362,61836008)
引用文本:
邱康,王子磊.基于车载图像的目标车辆压线检测方法.计算机系统应用,2019,28(11):188-194
QIU Kang,WANG Zi-Lei.Lane-Crossing Detection Method of Vehicles with In-Vehicle Image.COMPUTER SYSTEMS APPLICATIONS,2019,28(11):188-194

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