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Detecting Violent Scenes in Movies by Auditory and Visual Cues

  • Yu Gong
  • Weiqiang Wang
  • Shuqiang Jiang
  • Qingming Huang
  • Wen Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5353)

Abstract

To detect violence in movies, we present a three-stage method integrating visual and auditory cues. In our method, those shots with potential violent content are first identified according to universal film-making rules. A modified semi-supervised learning technique based on semi-supervised cross feature learning (SCFL) is exploited, since it is capable to combine different types of features and use unlabeled data to improve the classification performance. Then, typical violence-related audio effects are further detected for the candidate shots, and we manage to transform the confidences outputted by the classifiers of various audio events into a shot-based violence score. Finally, the first two-stage probabilistic outputs are integrated in a boosting way to generate the final inference. The experimental results on four typical action movies preliminarily show the effectiveness of our method.

Keywords

Violence Detection Semi-supervised Cross Feature Learning Audio Effects 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yu Gong
    • 1
    • 2
    • 3
  • Weiqiang Wang
    • 1
    • 2
    • 3
  • Shuqiang Jiang
    • 1
    • 2
  • Qingming Huang
    • 1
    • 2
    • 3
  • Wen Gao
    • 3
    • 4
  1. 1.Key Lab of Intell. Info. Process.Chinese Academy of SciencesBeijingChina
  2. 2.Institute of Computing TechnologyChinese Academy of SciencesBeijingChina
  3. 3.Graduate School of Chinese Academy of SciencesBeijingChina
  4. 4.Institute of Digital MediaPeking UniversityBeijingChina

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