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Title:
interactive event detection in crowd scenes
Author: Qin Lei ; Cheng Zhongwei ; Huang Qingming ; Pang Junbiao
Source: ACM International Conference Proceeding Series
Conference Name: 4th International Conference on Internet Multimedia Computing and Service, ICIMCS 2012
Conference Date: September 9, 2012 - September 11, 2012
Issued Date: 2012
Conference Place: Wuhan, China
Keyword: Airport security ; Internet ; Network security ; Security systems
Indexed Type: EI
ISBN: 9781450316002
Department: (1) Key Lab. of Intel. Inf. Proc. Institute of Computing Technology Chinese Academy of Sciences Beijing China; (2) Graduate University of Chinese Academy of Sciences Beijing China; (3) Beijing Municipal Key Lab. of Multimedia and Intelligent Software Technology Beijing Univ. of Tech. China
Sponsorship: ACM SIGMM China Chapter; Central China Normal University; National Science Foundation of China Academy of Sciences; NEC Laboratories China; Microsoft Research; Wuhan Daqian Information Technology Company Limited
Abstract: As an important aspect in video content analysis, event detection is still an open problem. In particular, the study on detecting interactive events in crowd scenes is still limited. In this paper, we investigate detecting interactive events between persons, e.g. PeopleMeet, PeopleSplitUp and Embrace in complex scenes using a sequence learning based approach. By sequence learning, the spatial-temporal context information is introduced in the learning stage. Experiments have been performed over TRECVid Event Detection 2010 dataset, which contains totally 144 hours surveillance video of London Gatwick airport. According to the TRECVid-ED 2010 formal evaluation, our approach obtains promising results, with the top performance (NDCR) for PeopleMeet and PeopleSplit-Up, and second-best performance (NDCR) for Embrace. Copyright © 2012 ACM.
English Abstract: As an important aspect in video content analysis, event detection is still an open problem. In particular, the study on detecting interactive events in crowd scenes is still limited. In this paper, we investigate detecting interactive events between persons, e.g. PeopleMeet, PeopleSplitUp and Embrace in complex scenes using a sequence learning based approach. By sequence learning, the spatial-temporal context information is introduced in the learning stage. Experiments have been performed over TRECVid Event Detection 2010 dataset, which contains totally 144 hours surveillance video of London Gatwick airport. According to the TRECVid-ED 2010 formal evaluation, our approach obtains promising results, with the top performance (NDCR) for PeopleMeet and PeopleSplit-Up, and second-best performance (NDCR) for Embrace. Copyright © 2012 ACM.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15812
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Qin Lei,Cheng Zhongwei,Huang Qingming,et al. interactive event detection in crowd scenes[C]. 见:4th International Conference on Internet Multimedia Computing and Service, ICIMCS 2012. Wuhan, China. September 9, 2012 - September 11, 2012.
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