ISCAS OpenIR
interactive event detection in crowd scenes
Qin Lei; Cheng Zhongwei; Huang Qingming; Pang Junbiao
2012
Conference Name4th International Conference on Internet Multimedia Computing and Service, ICIMCS 2012
SourceACM International Conference Proceeding Series
Pages46-49
Conference DateSeptember 9, 2012 - September 11, 2012
Conference PlaceWuhan, China
Indexed TypeEI
ISBN9781450316002
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
English AbstractAs 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.; 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.
KeywordAirport Security Internet Network Security Security Systems
SponsorshipACM 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
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15812
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Qin Lei,Cheng Zhongwei,Huang Qingming,et al. interactive event detection in crowd scenes[C],2012:46-49.
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