Zobrazeno 1 - 10
of 1 863
pro vyhledávání: '"motion recognition"'
Autor:
S. Vaijayanthi, J. Arunnehru
Publikováno v:
Automatika, Vol 65, Iss 3, Pp 1088-1099 (2024)
Relating specifically to human–computer interaction (HCI), computer vision research has placed a substantial emphasis on intelligent emotion recognition in recent years. The primary emphasis lies in investigating speech aspects and bodily motions,
Externí odkaz:
https://doaj.org/article/e1ff5969ba7f49a6856ecee6536fb1c8
Publikováno v:
AIMS Mathematics, Vol 9, Iss 7, Pp 17901-17916 (2024)
Lately, as a subset of human-centric studies, vision-oriented human action recognition has emerged as a pivotal research area, given its broad applicability in fields like healthcare, video surveillance, autonomous driving, sports, and education. Thi
Externí odkaz:
https://doaj.org/article/ccee04ac3c8e4a86a6166d54a99f0eea
Autor:
Xiao Fang, Yuzhen Guo
Publikováno v:
IEEE Access, Vol 12, Pp 107570-107582 (2024)
Traffic accidents are a serious issue in modern society, causing significant personal and property damage. To better understand and prevent these accidents, traffic accident restoration technology has been developed. This study employs a multidimensi
Externí odkaz:
https://doaj.org/article/bed7b495974d4baa82c0d94dc8657d67
Publikováno v:
IEEE Access, Vol 12, Pp 82730-82741 (2024)
Recognition of human intended motion is key to developing intelligent human-robot interaction (HRI) controllers in assistive devices. This study aims to develop a human motion recognition architecture tailored explicitly for real-time assistive robot
Externí odkaz:
https://doaj.org/article/2a0e3229da094821b4b6adfed2e410a8
Autor:
Chao Pei
Publikováno v:
IEEE Access, Vol 12, Pp 58690-58702 (2024)
Video motion recognition plays a crucial role in advanced sports analysis. With video motion recognition, sports analytics has become more data-driven and result-oriented, significantly enhancing the professionalism and efficiency in the sports domai
Externí odkaz:
https://doaj.org/article/cae8ccc54f244f4280349a8002662dda
Autor:
Sejin Kim, Wan Kyun Chung
Publikováno v:
IEEE Access, Vol 12, Pp 34342-34353 (2024)
Upper-limb position is one of the most critical factors that degrade sEMG-based motion recognition accuracy. Therefore, we propose an upper-limb position-robust motion recognition with unsupervised domain adaptation. The proposed method finds the fea
Externí odkaz:
https://doaj.org/article/afff1036aa584422a4e5320ad1d310a1
Autor:
Hyunsoo Yoon, Hyun-Chool Shin
Publikováno v:
Journal of Electromagnetic Engineering and Science, Vol 24, Iss 1, Pp 65-77 (2024)
This study aimed to detect fall risk behaviors using radar—a non-contact sensor—to prevent falling accidents, which are one of the most fatal problems faced by older adults. Hospitals and nursing homes often have patients who cannot move alone wi
Externí odkaz:
https://doaj.org/article/9ff22810d40b4a42bf5956357522eebc
Publikováno v:
IEEE Access, Vol 12, Pp 21673-21697 (2024)
Semantic video scene-understanding applications rely on object-camera motion recognition techniques for scene contextual movement representation. While existing machine learning-based methods perform efficiently, their primary limitation is to analyz
Externí odkaz:
https://doaj.org/article/b131b119d9334c5998263e4233633838
Publikováno v:
IEEE Access, Vol 12, Pp 5684-5707 (2024)
The central perspective of this review is to categorize research in Human Motion Recognition (HMR) over the past decade into two significant categories: vision sensor-based (VS) methods and wearable sensor-based (WS) methods. Within each category, re
Externí odkaz:
https://doaj.org/article/796a01c5a0d84bfe85c8791ad7ab720d
Autor:
Tao Peng
Publikováno v:
SLAS Technology, Vol 29, Iss 5, Pp 100181- (2024)
In the pursuit of advancing health and rehabilitation, the quintessence of human motion recognition technology has been underscored through its quantitative contributions to physical performance assessment. This research delineates the inception of a
Externí odkaz:
https://doaj.org/article/b3f7a582c2a942eeb1596326106df4e9