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  • 标题:Detection of Abnormal Behaviours in Crowd Scene: A Review
  • 本地全文:下载
  • 作者:N. N. A. Sjarif ; S. M. Shamsuddin. ; S. Z. Hashim
  • 期刊名称:International Journal of Advances in Soft Computing and Its Applications
  • 印刷版ISSN:2074-8523
  • 出版年度:2012
  • 卷号:4
  • 期号:1
  • 出版社:International Center for Scientific Research and Studies
  • 摘要:Crowd analysis becomes the most active-oriented research and trendy topic in computer vision nowadays. Typically, crowd is a unique group of individual or something involves community or society where the phenomena of the crowd are very familiar in a variety of research discipline such as sociology, civil and physics [1]. Within the crowd, there exist many behavior anomalies or abnormality. There are many ways of detecting these abnormalities such as crowd density estimation, crowd motion detection, crowd tracking and crowd behavior recognition. All of these protocols normally involve three steps: pre-processing, object detection and event/behavior recognition. In this paper, we provide state-of-the-art of crowd analysis from 2000 until now. Based on our analysis from these substantial reviews, we propose a general framework and pattern taxonomy of detecting abnormal behavior in a crowded environment accordingly.
  • 关键词:Video Surveillance; Crowd Scene; Crowd Analysis; Abnormal ;behavior
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