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@inproceedings{1634967,
author = {Grammalidis, Nikos and Kico, Iris and Liarokapis, Fotios},
address = {Not Specified},
booktitle = {Strategic Innovative Marketing and Tourism},
doi = {http://dx.doi.org/10.1007/978-3-030-36126-6_35},
editor = {Androniki Kavoura, Efstathios Kefallonitis, Prokopios Theodoridis},
keywords = {Human motion analysis from video; Artificial intelligence; Deep learning; Folk dance preservation; Applications},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Not Specified},
isbn = {978-3-030-36125-9},
pages = {321-329},
publisher = {Springer, Cham},
title = {Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances},
url = {https://link.springer.com/chapter/10.1007/978-3-030-36126-6_35},
year = {2020}
}
TY - JOUR
ID - 1634967
AU - Grammalidis, Nikos - Kico, Iris - Liarokapis, Fotios
PY - 2020
TI - Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances
PB - Springer, Cham
CY - Not Specified
SN - 9783030361259
KW - Human motion analysis from video
KW - Artificial intelligence
KW - Deep learning
KW - Folk dance preservation
KW - Applications
UR - https://link.springer.com/chapter/10.1007/978-3-030-36126-6_35
L2 - https://link.springer.com/chapter/10.1007/978-3-030-36126-6_35
N2 - Analysis of human motion is an important research area in computer vision with numerous applications. Recent projects, such as EU i-Treasures and TERPSICHORE projects conduct research in this field to improve the capture, analysis and presentation of Intangible Cultural Heritage (ICH) using ICT-based approaches. The final goal is to document these forms of intangible heritage and to capture the associated knowledge in order to safeguard and transmit this information to the next generations. In addition, these approaches can give rise to new services for research, education and cultural tourism. They can also be used by creative industries (e.g. companies performing film, video, TV or VR applications production), as well as by local communities, creating new local development opportunities by promoting local heritage. This paper first reviews some very recent state of the art approaches based on deep learning which can achieve impressive results in recovering human motion (2D or 3D) and structure (skeleton with joints or realistic 3D model of the human body). Based on such approaches, we then propose a dance analysis approach, currently under development in TERPSICHORE project. Preliminary results are presented and, finally, some conclusions are drawn.
ER -
GRAMMALIDIS, Nikos, Iris KICO a Fotios LIAROKAPIS. Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances. Online. In Androniki Kavoura, Efstathios Kefallonitis, Prokopios Theodoridis. \textit{Strategic Innovative Marketing and Tourism}. Not Specified: Springer, Cham, 2020, s.~321-329. ISBN~978-3-030-36125-9. Dostupné z: https://dx.doi.org/10.1007/978-3-030-36126-6\_{}35.
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