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Research on Action Recognition and Content Analysis in Videos Based on DNN and MLN

机译:基于DNN和MLN视频的动作识别与内容分析研究

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摘要

In the current era of multimedia information, it is increasingly urgent to realize intelligent video action recognition and content analysis. In the past few years, video action recognition, as an important direction in computer vision, has attracted many researchers and made much progress. First, this paper reviews the latest video action recognition methods based on Deep Neural Network and Markov Logic Network. Second, we analyze the characteristics of each method and the performance from the experiment results. Then compare the emphases of these methods and discuss the application scenarios. Finally, we consider and prospect the development trend and direction of this field.
机译:在当前的多媒体信息时代,越来越迫切地实现智能视频动作识别和内容分析。在过去几年中,视频行动识别作为计算机愿景的重要方向,吸引了许多研究人员并取得了很大进展。首先,本文评论了基于深神经网络和马尔可夫逻辑网络的最新视频动作识别方法。其次,我们分析了各种方法的特征和实验结果的性能。然后比较这些方法的重点并讨论应用程序方案。最后,我们考虑并展望该领域的发展趋势和方向。

著录项

  • 来源
    《Computers, Materials & Continua》 |2019年第3期|1189-1204|共16页
  • 作者单位

    School of Information Engineering Minzu University of China Beijing 100081 China National language resource monitoring &Research Center Minority Languages Branch Minzu University of China Beijing 100081 China;

    School of Electronic Information Engineering Beijing Jiaotong University Beijing 100044 China;

    School of Information Engineering Minzu University of China Beijing 100081 China National language resource monitoring &Research Center Minority Languages Branch Minzu University of China Beijing 100081 China;

    New Jersey Institute of Technology 323 Dr Martin Luther King Jr Blvd. Newark NJ 07102 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Video action recognition; deep learning network; markov logic network;

    机译:视频动作识别;深度学习网络;马尔可夫逻辑网络;

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