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Multimedia Tools and Applications

, Volume 78, Issue 1, pp 677–695 | Cite as

LSTM-based multi-label video event detection

  • An-An LiuEmail author
  • Zhuang Shao
  • Yongkang Wong
  • Junnan Li
  • Yu-Ting Su
  • Mohan Kankanhalli
Article
  • 387 Downloads

Abstract

Since large-scale surveillance videos always contain complex visual events, how to generate video descriptions effectively and efficiently without human supervision has become mandatory. To address this problem, we propose a novel architecture for jointly recognizing multiple events in a given surveillance video, motivated by the sequence to sequence network. The proposed architecture can predict what happens in a video directly without the preprocessing of object detection and tracking. We evaluate several variants of the proposed architecture with different visual features on a novel dataset perpared by our group. Moreover, we compute a wide range of quantitative metrics to evaluate this architecture. We further compare it to the popular Support Vector Machine-based visual event detection method. The comparison results suggest that the proposal method can outperform the traditional computer vision pipelines for visual event detection.

Keywords

Concurrent event detections Recurrent neural network 

Notes

Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (61772359, 61472275, 61572356), the Tianjin Research Program of Application Foundation and Advanced Technology (15JCYBJC16200), the National Research Foundation, Prime Minister Office, Singapore under its International Research Centre in Singapore Funding Initiative.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • An-An Liu
    • 1
    Email author
  • Zhuang Shao
    • 1
  • Yongkang Wong
    • 2
  • Junnan Li
    • 3
  • Yu-Ting Su
    • 1
  • Mohan Kankanhalli
    • 4
  1. 1.School of Electrical and Information EngineeringTianjin UniversityTianjinChina
  2. 2.Smart Systems InstituteNational University of SingaporeSingaporeSingapore
  3. 3.NUS Graduate School for Integrative Sciences and EngineeringNational University of SingaporeSingaporeSingapore
  4. 4.School of ComputingNational University of SingaporeSingaporeSingapore

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