@article{ART002998479},
author={Kunwoo Kim and Jonghyun Hong and Jonghyuk Park},
title={Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2023},
volume={28},
number={9},
pages={17-25},
doi={10.9708/jksci.2023.28.09.017}
TY - JOUR
AU - Kunwoo Kim
AU - Jonghyun Hong
AU - Jonghyuk Park
TI - Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning
JO - Journal of The Korea Society of Computer and Information
PY - 2023
VL - 28
IS - 9
PB - The Korean Society Of Computer And Information
SP - 17
EP - 25
SN - 1598-849X
AB - In this paper, we propose a model that can perform human pose estimation through a MobileViT-based model with fewer parameters and faster estimation. The based model demonstrates lightweight performance through a structure that combines features of convolutional neural networks with features of Vision Transformer. Transformer, which is a major mechanism in this study, has become more influential as its based models perform better than convolutional neural network-based models in the field of computer vision. Similarly, in the field of human pose estimation, Vision Transformer-based ViTPose maintains the best performance in all human pose estimation benchmarks such as COCO, OCHuman, and MPII. However, because Vision Transformer has a heavy model structure with a large number of parameters and requires a relatively large amount of computation, it costs users a lot to train the model. Accordingly, the based model overcame the insufficient Inductive Bias calculation problem, which requires a large amount of computation by Vision Transformer, with Local Representation through a convolutional neural network structure. Finally, the proposed model obtained a mean average precision of 0.694 on the MS COCO benchmark with 3.28 GFLOPs and 9.72 million parameters, which are 1/5 and 1/9 the number compared to ViTPose, respectively.
KW - Deep Learning;Computer Vision;Keypoint Detection;Human Pose Estimation;Vision Transformer
DO - 10.9708/jksci.2023.28.09.017
ER -
Kunwoo Kim, Jonghyun Hong and Jonghyuk Park. (2023). Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning. Journal of The Korea Society of Computer and Information, 28(9), 17-25.
Kunwoo Kim, Jonghyun Hong and Jonghyuk Park. 2023, "Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning", Journal of The Korea Society of Computer and Information, vol.28, no.9 pp.17-25. Available from: doi:10.9708/jksci.2023.28.09.017
Kunwoo Kim, Jonghyun Hong, Jonghyuk Park "Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning" Journal of The Korea Society of Computer and Information 28.9 pp.17-25 (2023) : 17.
Kunwoo Kim, Jonghyun Hong, Jonghyuk Park. Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning. 2023; 28(9), 17-25. Available from: doi:10.9708/jksci.2023.28.09.017
Kunwoo Kim, Jonghyun Hong and Jonghyuk Park. "Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning" Journal of The Korea Society of Computer and Information 28, no.9 (2023) : 17-25.doi: 10.9708/jksci.2023.28.09.017
Kunwoo Kim; Jonghyun Hong; Jonghyuk Park. Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning. Journal of The Korea Society of Computer and Information, 28(9), 17-25. doi: 10.9708/jksci.2023.28.09.017
Kunwoo Kim; Jonghyun Hong; Jonghyuk Park. Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning. Journal of The Korea Society of Computer and Information. 2023; 28(9) 17-25. doi: 10.9708/jksci.2023.28.09.017
Kunwoo Kim, Jonghyun Hong, Jonghyuk Park. Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning. 2023; 28(9), 17-25. Available from: doi:10.9708/jksci.2023.28.09.017
Kunwoo Kim, Jonghyun Hong and Jonghyuk Park. "Lightening of Human Pose Estimation Algorithm Using MobileViT and Transfer Learning" Journal of The Korea Society of Computer and Information 28, no.9 (2023) : 17-25.doi: 10.9708/jksci.2023.28.09.017