Many people engage in self-directed sports training at home but lack the real-time guidance of professional coaches, making them susceptible to injuries or the development of incorrect habits. In this paper, we propose a novel application framework called MAAIG(Motion Analysis And Instruction Generation). It can generate embedding vectors for each frame based on user-provided sports action videos. These embedding vectors are associated with the 3D skeleton of each frame and are further input into a pretrained T5 model. Ultimately, our model utilizes this information to generate specific sports instructions. It has the capability to identify potential issues and provide real-time guidance in a manner akin to professional coaches, helping users improve their sports skills and avoid injuries.
@article{arxiv.2311.00980,
title = {MAAIG: Motion Analysis And Instruction Generation},
author = {Wei-Hsin Yeh and Pei Hsin Lin and Yu-An Su and Wen Hsiang Cheng and Lun-Wei Ku},
journal= {arXiv preprint arXiv:2311.00980},
year = {2023}
}
Comments
Accepted to the ACM Multimedia Asia 2023 Workshop on Intelligent Sports Technologies (WIST)