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Human Action Recognition: A Survey

  • Meixia FuEmail author
  • Na Chen
  • Zhongjie Huang
  • Kaili Ni
  • Yuhao Liu
  • Songlin Sun
  • Xiaomei Ma
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 550)

Abstract

In this paper, we provide a comprehensive survey in human action recognition and prediction, which has always been a universal and critical area in computer vision. Human action recognition is the first step for a machine to understand and percept the nature, which is small part in machine perception. Human action prediction is the higher layer than human action recognition that is small part in machine cognition, which would give the machine the ability of imagination and reasoning. Here, we only discuss human action recognition from two methodologies that is based on presentations and deep learning, separately. Then, 4 public datasets of human action recognition are descripted closely. Some challenges in dataset are also proposed because of the significance to the development of computer vision. Meanwhile, we compare and summarize recent-published research achievements under deep learning. In the end, we conclude about mentioned methods and future challenges to work on for computer vision.

Keywords

Human action recognition Computer vision Machine perception Human action prediction Machine cognition Deep learning 

Notes

Acknowledgment

This work is supported by National Natural Science Foundation of China (Project61471066) and the open project fund (No. 201600017) of the National Key Laboratory of Electromagnetic Environment, China.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Meixia Fu
    • 1
    • 2
    • 3
    Email author
  • Na Chen
    • 1
    • 2
    • 3
  • Zhongjie Huang
    • 1
    • 2
    • 3
  • Kaili Ni
    • 1
    • 2
    • 3
  • Yuhao Liu
    • 1
    • 2
    • 3
  • Songlin Sun
    • 1
    • 2
    • 3
  • Xiaomei Ma
    • 4
  1. 1.National Engineering Laboratory for Mobile Network SecurityBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of EducationBeijing University of Posts and TelecommunicationsBeijingChina
  3. 3.School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina
  4. 4.China United Network Communications Group Co., Ltd.BeijingChina

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