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文章基本信息

  • 标题:Abnormal Crowd Motion Behaviour Detection based on SIFT Flow
  • 本地全文:下载
  • 作者:Dongping Zhang ; Kaihang Xu ; Huailiang Peng
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2016
  • 卷号:9
  • 期号:1
  • 页码:289-302
  • DOI:10.14257/ijsip.2016.9.1.28
  • 出版社:SERSC
  • 摘要:This paper focuses on the detection of the abnormal motion behaviour recognition of the crowd, and proposes an innovation method which is consist of three steps, i.e. SIFT flow + weighted orientation histogram + Hidden Markov Model(HMM). Analogous to optical flow, which is used to get the motion information of the pixels from two adjacent frames, SIFT flow is of higher precision. Next, we build up a a weighted orientation histogram as a statistical measurement for the SIFT flow features from the first step. Finally, the derived histogram is taken as the input for HMM in preparation for the detection of abnormal crowd motion. Experimental results show that compared to the existing method, our proposed one can detect the abnormal motion behaviour more effectively.
  • 关键词:SIFT flow; coarse to fine; dense scene correspondence; HMM; crowd ; motion behaviour detection; weighted orientation histogram
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