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A Method Based on Dense Trajectory for Violent Video Classification

机译:一种基于密集轨迹的抗脉冲轨迹的方法

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At present, the internet technology develops so rapidly and the video becomes the major component of the internet traffic. The content security of massive public videos is an important factor to the social stability. Among them, violent video is an important class of unsafe videos. We proposed a novel method based on dense trajectory and extreme learning machine to recognize them. The spatial-temporal characteristics were well expressed by the use of optical flow and gradient. The experiment on the benchmark dataset named Movies indicated our proposed method had a better accuracy than the state-of-the-art methods. Our proposed method is an efficient method for violent video classification.
机译:目前,互联网技术发展如此迅速,视频成为互联网流量的主要组成部分。大规模公开视频的内容安全是社会稳定的重要因素。其中,暴力视频是一类重要的不安全视频。我们提出了一种基于密集轨迹和极端学习机的新方法来识别它们。通过使用光学流动和梯度,很好地表达了空间的特征。基准数据集的实验指定了电影表明我们的建议方法具有比最先进的方法更好的准确性。我们所提出的方法是一种有效的剧烈视频分类方法。

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