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  • 标题:Real-time people counting using blob descriptor
  • 本地全文:下载
  • 作者:Satoshi Yoshinaga ; Satoshi Yoshinaga ; Atsushi Shimada
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2010
  • 卷号:2
  • 期号:1
  • 页码:143-152
  • DOI:10.1016/j.sbspro.2010.01.028
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWe propose a system for counting the number of pedestrians in real-time. This system estimates “how many pedestrians are and where they are in video sequences” by the following procedures. First, candidate regions are segmented into blobs according to background subtraction. Second, a set of features are extracted from each blob and a neural network estimates the number of pedestrians corresponding to each set of features. To realize real-time processing, we used only simple and valid features, and the adaptive background modeling using Parzen density estimation, which realizes fast and accurate object detection in input images. We also validate the effectiveness of the proposed system by several experiments.
  • 关键词:Visual surveillance;People detection;People counting
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