基于视频的特定区域入侵检测

Hang Chen, Dongfang Chen, Xiaofeng Wang
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引用次数: 9

摘要

为了解决视频中复杂场景下的目标检测和目标跟踪问题,本文在传统高斯混合模型的基础上提出了一种改进高斯混合模型算法的方法。在更新模型时,根据连续视频帧的特点,将背景模型划分为静态区域和动态区域,并采用不同的策略更新背景。然后,本文提出了一种入侵检测算法。入侵是通过目标的质心是否在特定区域来判断的。如果质心位于区域外,则表明目标没有入侵该特定区域,否则表明目标入侵了该特定区域。如果是,系统触发告警,并在视频帧上显示标签信息。实验表明,该算法可以实现特定区域的入侵检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intrusion detection of specific area based on video
In order to solve the problems of object detection and object tracking under complex scenes in video, this paper proposes a way to improve Gaussian Mixture Model algorithm based on the traditional Gaussian Mixture Model. When the model is updated, according to the characteristics of continuous video frame, the background model is divided into static regions and dynamic regions, and the background is updated in different strategies. Then, this paper presents an algorithm for the intrusion detection. Intrusion is judged by whether the centroid of the target is in the specific area. If the centroid is located outside the area, it shows that the target does not invade the specific area, otherwise the target invades the specific area. If so, the system triggers alarm and label information appear on the video frames. Experiments show that this algorithm can realize the intrusion detection of specific area.
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