Real-time people counting using blob descriptor

研究成果: ジャーナルへの寄稿Conference article

18 引用 (Scopus)

抄録

We 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.

元の言語英語
ページ(範囲)143-152
ページ数10
ジャーナルProcedia - Social and Behavioral Sciences
2
発行部数1
DOI
出版物ステータス出版済み - 8 2 2010
イベント1st International Conference on Security Camera Network, Privacy Protection and Community Safety 2009, SPC2009 - Kiryu, 日本
継続期間: 10 28 200910 30 2009

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pedestrian
neural network
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Pedestrians

All Science Journal Classification (ASJC) codes

  • Social Sciences(all)
  • Psychology(all)

これを引用

Real-time people counting using blob descriptor. / Yoshinaga, Satoshi; Shimada, Atsushi; Taniguchi, Rin-Ichiro.

:: Procedia - Social and Behavioral Sciences, 巻 2, 番号 1, 02.08.2010, p. 143-152.

研究成果: ジャーナルへの寄稿Conference article

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