Complex Event Detection in Video Streams

Jia Ke, Xiao Jun Chen, Bao-Ding Chen, Hui Xu, Jian-Guo Zhang, Xiao-Ming Jiang, Manrong Wang, Xiaobo Chen, Qian-Qian Zhang, Wen-Hong Cai
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引用次数: 2

Abstract

With the development of monitoring camera and the update of hardware, the processing of video data is becoming more and more. It is an important topic to detect the event in the video data and analyze its intrinsic relationship in order to form a semantic description. Complex event detection in video includes detection of video events, description of target features, and finding the concept of semantic. Based on the hypergraph theory, this paper put forward the characteristics of the construction of track and multi label hypergraph description of the moving target, and classification of video events. The experimental results show that, in comparison with other methods including ordinary graph based method and hypergraph based multi-label semi-supervised learning method, our method achieves better average precision and average recall when detecting complex events.
视频流中的复杂事件检测
随着监控摄像机的发展和硬件的更新,视频数据的处理变得越来越复杂。如何检测视频数据中的事件并分析其内在关系,从而形成语义描述是一个重要的课题。视频中的复杂事件检测包括视频事件的检测、目标特征的描述和语义概念的发现。基于超图理论,提出了运动目标的轨迹构造和多标签超图描述以及视频事件分类的特点。实验结果表明,与基于普通图的方法和基于超图的多标签半监督学习方法相比,该方法在检测复杂事件时具有更好的平均准确率和平均召回率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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