論文

査読有り
2013年1月

Deciphering the Crowd: Modeling and Identification of Pedestrian Group Motion

SENSORS
  • Zeynep Yuecel
  • ,
  • Francesco Zanlungo
  • ,
  • Tetsushi Ikeda
  • ,
  • Takahiro Miyashita
  • ,
  • Norihiro Hagita

13
1
開始ページ
875
終了ページ
897
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.3390/s130100875
出版者・発行元
MDPI AG

Associating attributes to pedestrians in a crowd is relevant for various areas like surveillance, customer profiling and service providing. The attributes of interest greatly depend on the application domain and might involve such social relations as friends or family as well as the hierarchy of the group including the leader or subordinates. Nevertheless, the complex social setting inherently complicates this task. We attack this problem by exploiting the small group structures in the crowd. The relations among individuals and their peers within a social group are reliable indicators of social attributes. To that end, this paper identifies social groups based on explicit motion models integrated through a hypothesis testing scheme. We develop two models relating positional and directional relations. A pair of pedestrians is identified as belonging to the same group or not by utilizing the two models in parallel, which defines a compound hypothesis testing scheme. By testing the proposed approach on three datasets with different environmental properties and group characteristics, it is demonstrated that we achieve an identification accuracy of 87% to 99%. The contribution of this study lies in its definition of positional and directional relation models, its description of compound evaluations, and the resolution of ambiguities with our proposed uncertainty measure based on the local and global indicators of group relation.

Web of Science ® 被引用回数 : 18

リンク情報
DOI
https://doi.org/10.3390/s130100875
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000314024800050&DestApp=WOS_CPL
URL
http://dblp.uni-trier.de/db/journals/sensors/sensors13.html#journals/sensors/YucelZIMH13