@inproceedings{ec184bd740db4bb089d04d79ed984655,
title = "Improving the Accuracy of Gait Detection Using Computer Vision",
abstract = "Using computer vision for gait analysis is easier and more cost-effective to implement in the field than using wearable devices or motion capture, etc. OpenPose is one of the freely available skeletal detection algorithms, but the accuracy of skeletal detection is not always high. Therefore, in this paper, the gait cycle is derived from the skeletal coordinate data obtained by general OpenPose. Based on the gait cycle, we propose a method to predict the coordinates and correct the skeletal coordinates.",
keywords = "Gait Analysis, OpenPose, Skeleton Detection, Video Processing",
author = "Sota Sugiyama and Yuna Ogiso and Masataka Yamamoto and Yuto Ishige and Hiroshi Takemura and Naoyuki Aikawa",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Region 10 Symposium, TENSYMP 2023 ; Conference date: 06-09-2023 Through 08-09-2023",
year = "2023",
doi = "10.1109/TENSYMP55890.2023.10223625",
language = "English",
series = "2023 IEEE Region 10 Symposium, TENSYMP 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE Region 10 Symposium, TENSYMP 2023",
}