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:2019,28(6):82-88
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基于高速公路场景的车辆目标跟踪
(1.长安大学 信息工程学院, 西安 710064;2.陕西省交通建设集团公司, 西安 710064)
Vehicle Object Tracking Method Based on Highway Scenario
(1.School of Information Engineering, Chang'an University, Xi'an 710064, China;2.Shaanxi Provincial Communications Construction Group Corporation, Xi'an 710064, China)
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投稿时间:2018-10-16    修订日期:2018-11-06
中文摘要: 车辆目标检测与跟踪是高速公路视频监控系统实时监控获取交通参数的关键步骤.本文提出了一种面向高速公路场景的目标轨迹时序信息结合核相关滤波KCF算法的车辆目标跟踪方法,实现了车辆目标的高精度持续跟踪.该方法首先采用基于深度学习的单目标检测SSD算法,通过建立车辆数据集,实现了适用于高速公路场景的车辆目标的分类与检测.然后,基于目标轨迹时序信息实现目标车辆与轨迹的匹配,并且采用KCF跟踪算法对丢失目标进行预测重定位,从而实现车辆目标轨迹的持续跟踪.实验表明,该跟踪方法精度高,且适应多种不同场景,具有较高的应用价值.
中文关键词: 目标跟踪  SSD  目标检测  KCF
Abstract:Vehicle object detection and tracking is a key step for the real-time monitoring and acquisition of traffic parameters in the video monitoring system of expressway. A vehicle tracking method based on trajectory temporal information with KCF algorithm is proposed to realize high precision continuous tracking. Firstly, data sets is established, the classification and detection of vehicle applicable to highway scenario are realized by using SSD algorithm based on deep learning. Then, based on the trajectory of temporal information, matching between object and trajectory is realized, and KCF algorithm is applied to forecast the missing object positioning, so as to realize the vehicle trajectory tracking. The experiment result shows that this tracking method has high precision, can adapt to many different scenarios, thus has high application value.
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基金项目:国家自然科学基金(61572083);陕西省重点研发计划重点项目(2018ZDXM-GY-047);中央高校团队培育项目(300102248402)
引用文本:
宋焕生,李莹,杨瑾,云旭,张韫,解熠.基于高速公路场景的车辆目标跟踪.计算机系统应用,2019,28(6):82-88
SONG Huan-Sheng,LI Ying,YANG Jin,YUN Xu,ZHANG Yun,XIE Yi.Vehicle Object Tracking Method Based on Highway Scenario.COMPUTER SYSTEMS APPLICATIONS,2019,28(6):82-88

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