Predicting Violence Rating Based on Pairwise Comparison

DOI Web Site 参考文献45件 オープンアクセス
  • JI Ying
    Graduate School of Informatics, Nagoya University
  • WANG Yu
    College of Information Science and Engineering, Ritsumeikan University
  • KATO Jien
    College of Information Science and Engineering, Ritsumeikan University
  • MORI Kensaku
    Graduate School of Informatics, Nagoya University

抄録

<p>With the rapid development of multimedia, violent video can be easily accessed in games, movies, websites, and so on. Identifying violent videos and rating violence extent is of great importance to media filtering and children protection. Many previous studies only address the problems of violence scene detection and violent action recognition, yet violence rating problem is still not solved. In this paper, we present a novel video-level rating prediction method to estimate violence extent automatically. It has two main characteristics: (1) a two-stream network is fine-tuned to construct effective representations of violent videos; (2) a violence rating prediction machine is designed to learn the strength relationship among different videos. Furthermore, we present a novel violent video dataset with a total of 1,930 human-involved violent videos designed for violence rating analysis. Each video is annotated with 6 fine-grained objective attributes, which are considered to be closely related to violence extent. The ground-truth of violence rating is given by pairwise comparison method. The dataset is evaluated in both stability and convergence. Experiment results on this dataset demonstrate the effectiveness of our method compared with the state-of-art classification methods.</p>

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