MAAIG: Motion Analysis And Instruction Generation
Wei-Hsin Yeh Pei Hsin Lin Yu-An Su Wen Hsiang Cheng Lun-Wei Ku
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.