Autor: |
Jin Y; Division of Information and Electronic Engineering, Muroran Institute of Technology, Muroran 050-8585, Japan., Suzuki G; Division of Information and Electronic Engineering, Muroran Institute of Technology, Muroran 050-8585, Japan., Shioya H; Division of Information and Electronic Engineering, Muroran Institute of Technology, Muroran 050-8585, Japan. |
Jazyk: |
angličtina |
Zdroj: |
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Jul 20; Vol. 22 (14). Date of Electronic Publication: 2022 Jul 20. |
DOI: |
10.3390/s22145402 |
Abstrakt: |
Various genres of dance, such as Yosakoi Soran, have contributed to the health of many people and contributed to their sense of belonging to a community. However, due to the effects of COVID-19, various face-to-face activities have been restricted and group dance practice has become difficult. Hence, there is a need to facilitate remote dance practice. In this paper, we propose a system for detecting and visualizing the very important dance motions known as stops. We measure dance movements by motion capture and calculate the features of each movement based on velocity and acceleration. Using a neural network to learn motion features, the system detects stops and visualizes them using a human-like 3D model. In an experiment using dance data, the proposed method obtained highly accurate stop detection results and demonstrated its effectiveness as an information and communication technology support for remote group dance practice. |
Databáze: |
MEDLINE |
Externí odkaz: |
|
Nepřihlášeným uživatelům se plný text nezobrazuje |
K zobrazení výsledku je třeba se přihlásit.
|