本文已被:浏览 1398次 下载 2152次
Received:May 22, 2017 Revised:June 08, 2017
Received:May 22, 2017 Revised:June 08, 2017
中文摘要: 针对视频监控中人群异常行为检测方面存在的实时性和准确性问题,本文基于金字塔LK光流法提出一种动态帧间间隔更新的人群异常行为检测的方法. 该算法通过提取的人群运动信息来动态更新帧间间隔,接着以该帧间间隔来检测人群运动信息. 这样,算法不仅保留了原算法在检测人群运动信息方面优点,且有效提高了算法的运行效率. 最后,该算法通过获取的人群运动矢量交点密集度及能量信息来识别人群异常行为. 对多个视频进行测试,测试结果表明,该算法能够以较高正确率识别视频中人群的异常行为,同时还有效提高了算法的运行速度.
Abstract:In order to detect the abnormal crowd behavior in video surveillance in real time and more accurate, this study proposes a method of dynamic interframe space updating based on the Pyramid LK optical flow. The algorithm dynamically updates the interframe interval by extracting the crowd motion information, and then detects the crowd motion information at the interframe interval. In this way, the algorithm does not only preserve the advantages of the traditional algorithm in detecting crowd motion information, but also improves the efficiency. Finally, the algorithm identifies the abnormal crowd behavior by acquiring the intersection density and energy information of the crowd motion vector. By testing multiple videos, the test results show that the algorithm can identify the abnormal crowd behavior in the video with high accuracy, and also effectively improves the running speed.
文章编号: 中图分类号: 文献标志码:
基金项目:省科技厅区域科技重大项目(2015H4007)
引用文本:
陈颖熙,廖晓东,钟帅.基于动态帧间间隔更新的人群异常行为检测.计算机系统应用,2018,27(2):207-211
CHEN Ying-Xi,LIAO Xiao-Dong,ZHONG Shuai.Abnormal Crowd Behavior Detection Based on Dynamic Interframe Spacing Updating.COMPUTER SYSTEMS APPLICATIONS,2018,27(2):207-211
陈颖熙,廖晓东,钟帅.基于动态帧间间隔更新的人群异常行为检测.计算机系统应用,2018,27(2):207-211
CHEN Ying-Xi,LIAO Xiao-Dong,ZHONG Shuai.Abnormal Crowd Behavior Detection Based on Dynamic Interframe Spacing Updating.COMPUTER SYSTEMS APPLICATIONS,2018,27(2):207-211