For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Low-Cost Method for Recognizing Table Tennis Activity
Se-Min LIM Jooyoung PARK Hyeong-Cheol OH
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2019/10/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Artificial Intelligence, Data Mining
activity recognition, sports skill assessment, wearable technology, cosine similarity, recurrent neural network,
Full Text: PDF>>
This study designs a low-cost portable device that functions as a coaching assistant system which can support table tennis practice. Although deep learning technology is a promising solution to realizing human activity recognition, we propose using cosine similarity in making inferences. Our experiments show that the cosine similarity based inference can be a good alternative to the deep learning based inference for the assistant system when resources are limited.