摘要
针对传统异常行为自动检测方法的准确率和稳定性无法满足多变视频检测需求的问题,将最新的目标检测网络YOLOv3与目标跟踪算法相结合,通过对基于SORT多目标跟踪框架的改进,对检测目标的级联匹配采用了融合运动与外观特征的指标,以适应实际高架桥梁道路监控的情况。然后利用改进的多目标跟踪算法,对城市高架道路监控视频中的目标进行跟踪,配合相应的轨迹判别规则实现对视频中出现的行人、停车和车辆变道的交通行为异常情况的自动判别,具有较高的判别精度,可以达到实际应用目的。
Aiming at the problem that the accuracy and stability of the traditional automatic detection method of abnormal behavior cannot meet various demand of video detection,this paper combined the latest target detection network YOLOv3 with the target tracking algorithm.Through the improvement of the multi-target tracking framework based on SORT,the cascade matching of detection targets adopted the index of fusion of motion and appearance features to adapt to the actual situation of via-duct road monitoring.Then,it used the improved multi-target tracking algorithm to track the target in the monitoring video of urban elevated road.With the corresponding trajectory discrimination rules,it realized the automatic discrimination of abnormal traffic behaviors of pedestrians,parking and vehicles changing lanes in the video.It has high discrimination accuracy and can achieve practical application purposes.
作者
高新闻
沈卓
许国耀
封玲
Gao Xinwen;Shen Zhuo;Xu Guoyao;Feng Ling(Institute of Mechanical&Electrical Engineering&Automation,Shanghai University,Shanghai 200444,China;SHU-SUCG Research Center for Building Industrialization,Shanghai University,Shanghai 200072,China;SHU-UTS SILC Business School,Shanghai University,Shanghai 201800,China;Shanghai Pujiang Bridge&Tunnel Operation Management Co.Ltd.,Shanghai 201315,China)
出处
《计算机应用研究》
CSCD
北大核心
2021年第6期1879-1883,共5页
Application Research of Computers
基金
上海市科委项目(18DZ1201204)。
