Exercise Recognition System using Facial Image Information
Kaho Kato, Chengshuo Xia, Yuta Sugiura
Reference / 引用するならこちら
Kaho Kato, Chengshuo Xia, Yuta Sugiura, Exercise Recognition System using Facial Image Information from a Mobile Device, The 2021 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2021), IEEE, March 9-11 2021, Nara, Japan. [DOI]
Daily exercise has played a significant role for people to stay healthy, however, some people cannot do moderate exercise continuously. In this paper, we propose an exercise recognition system using facial image information for making exercise management convenient. The proposed system gets facial image information from a built-in camera on a mobile device, can recognize and classify multiple kinds of exercises. When a user exercises in a condition where the face is within an angle of view, the system extracts features from the facial images. Via the evaluation experiment with the data of a user, the average classification accuracy can reach up to 97.2%. To improve the operation of the designed system, we also evaluated the suitable window size, the dimension reduction, and the influence of the user’s standing position.