@inproceedings{5b5c4d40ff034fb7a44d5355801623ac,
title = "Action Recognition Algorithm based on 2D Human Pose Estimation Method",
abstract = "This paper presents an action recognition method based on 2D human body node data in video. This method uses the pose estimation algorithm to detect the human body node data in each frame of video information. We get the two-dimensional coordinates and confidence data of the nodes, and optimize the arrangement of these data into a 3D array form similar to images. Finally, we use the classical two-dimensional convolutional neural network to carry out classification training. The test on UCF-101 data set shows that this method can indeed improve the accuracy of action recognition based on RGB information to a certain extent, and reduce the training cost.",
keywords = "Action recognition, Pose estimation, Two-dimensional convolutional neural network",
author = "Chongkai Yu and Wenjie Chen and Ye Li and Chen Chen",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9550204",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7366--7370",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "United States",
}