The Application of Action Recognition Based on MPP-YOLOv3 Algorithm in Posture Correction
DOI:
https://doi.org/10.31449/inf.v48i10.5919Abstract
Posture recognition, as a research hotspot, has been widely applied. A recognition model based on bone key point detection is proposed for the posture correction application module. Firstly, the lightweight You Only Look Once v3 Tiny network was chosen as the infrastructure, and the OpenPose algorithm in the bottom-up strategy was chosen to implement posture recognition. To reduce the computational burden of the model, the Media Pipe Blaze Pose algorithm was introduced for improvement. At the same time, by refining more bone key points, the accuracy of the model has been improved. The experiment outcomes said the recognition accuracy of Cross View in the NTU60 RGB+D dataset and NTU120 RGB+D dataset was 94.7% and 82.7%, respectively. Compared to graph Transformer networks and semantic posture recognition models, the Cross Subject metric has improved by an average of 3.5%. Therefore, the research and design model has shown better robustness in the field of posture recognition, which can help complete pose correction more efficiently.
Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika
