南京理工大学学报（自然科学版）2017，Vol.41Issue(1)：65-73,79,10.DOI:10.14177/j.cnki.32-1397n.2017.41.01.009
基于视频图像的公交车人群异常情况检测
Video-based abnormal crowd behavior detection on bus
沈铮 1吴薇1
作者信息
- 1. 江南大学 物联网工程学院,江苏 无锡 214122
- 折叠
摘要
Abstract
In order to strengthen the bus safety precautions,this paper presents an image processing based detection algorithm to detect the anomalous crowd behavior which mainly refers to the rapid flow of the crowd in the bus.According to the trajectory of passengers,region of interest is determined.Moving targets are extracted and data processing range is reduced with an improved ViBe algorithm.The Shi-Tomasi corner detection algorithm is used to extract keypoints.Through pyramid Lucas-Kanade optical flow with correction coefficients,speed information is collected to recognize anomalous behavior.Experimental results show that the improved ViBe algorithm has more robustness to illumination than the ViBe algorithm and the accuracy of the proposed algorithm is more than 86.4%.关键词
人群异常/感兴趣区域/运动目标检测/角点检测/光流法Key words
anomalous crowd/region of interest/moving target detection/corner detection/optical flow分类
信息技术与安全科学引用本文复制引用
沈铮,吴薇..基于视频图像的公交车人群异常情况检测[J].南京理工大学学报（自然科学版）,2017,41(1):65-73,79,10.
