基于光流法的异常行为检测算法

Lu Yu, Yali Wang, Jie Li, Ye Tian
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引用次数: 0

摘要

本文提出了一种基于光流法的异常行为自动检测算法。通过比较图像的“动量”和阈值,算法可以判断是否发生异常运动。为了提高实时性,该算法通过降低图像分辨率、设置感兴趣区域(ROI)和忽略光流点的微小变化来实现异常行为的实时视频检测。采用计算累积报警代替单帧图像报警,有效地避免了误判。通过对电梯异常行为视频的仿真,验证了该算法的可行性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm of Detecting Abnormal Behavior Based on Optical Flow Method
In this paper, an algorithm of detecting abnormal behavior based on optical flow method for the automatic monitoring is proposed. By comparing the "momentum" of the image and the threshold, the algorithm can determine whether abnormal motion occurs or not. For improving the real-time performance, the algorithm which can be applied to real-time video detection of abnormal behavior, reduces the image resolution, sets the region of interest (ROI) and ignores the tiny changes of optical flow points. Furthermore, calculating accumulating alarm is used instead of single frame image alarm, so the misjudgment is avoided effectively. The feasibility and accuracy of the algorithm are verified through the simulation of abnormal behavior video in elevator.
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