摘要
密集人群场景下的视频异常事件检测是当今智能监控技术研究中的一个热点。本文针对如何合理提取面向密集人群场景视频的时空特征、以及提高密集人群异常检测的效率进行研究,结合人类视觉感知系统相关知识,分析了将视频的时间特征和空间特征相融合的四元数傅里叶变换,提出了一种新的适用于密集人群场景的特征提取方法。最后通过实验证明,本文所提出的特征能够较为全面准确地描述密集人群视频场景中的特征,并取得了良好的异常检测效果。
Abnormal crowd behavior detection is a highlv focused research area of the intelligent monitoring .The paper mainly aims at studying how to extract spatio‐temporal characteristics of dense crowd video ,and how to improve the efficiency of anomaly detection .Combining with human visual system（HVS） ,we proposed a novel method based on the analysis of the quaternion Fourier transform which is a fusion of spatio‐temporal characteristics in order to extract features of dense crowd scene .It is proved by the experiment that the proposed method can describe the dense crowd scene from different aspects and achieve good effect of anomaly detection as well .
出处
《电子测量技术》
2016年第7期72-75,80,共5页
Electronic Measurement Technology
关键词
密集人群视频
四元数傅里叶变换
特征提取
dense crowd video
quaternion Fourier transform
feature extraction
