English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 54059/88894 (61%)
造访人次 : 10549786      在线人数 : 14
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻

    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/97001

    题名: Abnormal Event Detection Using HOSF
    作者: Yen, Shwu-Huey;Wang, Chun-Hui
    贡献者: 淡江大學資訊工程學系
    关键词: normality;crowd;social force (SF);histogram of oriented social force (HOSF);z-value
    日期: 2013-12-16
    上传时间: 2014-03-14 16:25:32 (UTC+8)
    摘要: In this paper a simple and effective crowd behavior normality method is proposed. We use the histogram of oriented social force (HOSF) as the feature vector to encode the observed events of a surveillance video. A dictionary of codewords is trained to include typical HOSFs. To detect whether an event is normal is accomplished by comparing how similar to the closest codeword via z-value. The proposed method includes the following characteristic: (1) the training is automatic without human labeling; (2) instead of object tracking, the method integrates particles and social force as feature descriptors; (3) z-score is used in measuring the normality of events. The method is testified by the UMN dataset with promising results.
    關聯: Proceedings of the International Conference on IT Convergence and Security (ICITCS 2013), 4p.
    显示于类别:[資訊工程學系暨研究所] 會議論文


    档案 描述 大小格式浏览次数
    Abnormal Event Detection Using HOSF.pdf635KbAdobe PDF611检视/开启



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈