Analysis of Human Motion Based on AI Technologies: Applications
for Safeguarding Folk Dance Performances

D 2020

Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances

GRAMMALIDIS, Nikos; Iris KICO a Fotios LIAROKAPIS

Základní údaje

Originální název

Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances

Autoři

GRAMMALIDIS, Nikos; Iris KICO a Fotios LIAROKAPIS

Vydání

Not Specified, Strategic Innovative Marketing and Tourism, od s. 321-329, 9 s. 2020

Nakladatel

Springer, Cham

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/20:00115410

Organizační jednotka

Fakulta informatiky

ISBN

978-3-030-36125-9

ISSN

DOI

https://doi.org/10.1007/978-3-030-36126-6_35

EID Scopus

2-s2.0-85126113393

Klíčová slova anglicky

Human motion analysis from video; Artificial intelligence; Deep learning; Folk dance preservation; Applications

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 31. 5. 2022 14:25, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

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.

Návaznosti

691218, interní kód MU

Název: Transforming Intangible Folkloric Performing Arts into Tangible Choreographic Digital (Akronym: Terpsichore)

Investor: Evropská unie, Transforming Intangible Folkloric Performing Arts into Tangible Choreographic Digital, MSCA Marie Skłodowska-Curie Actions (Excellent Science)

Citovat

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. Strategic Innovative Marketing and Tourism. Not Specified: Springer, Cham, 2020, s. 321-329. ISBN 978-3-030-36125-9. Dostupné z: https://doi.org/10.1007/978-3-030-36126-6_35.

@inproceedings{1634967,
   author = {Grammalidis, Nikos and Kico, Iris and Liarokapis, Fotios},
   address = {Not Specified},
   booktitle = {Strategic Innovative Marketing and Tourism},
   doi = {https://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  - CONF
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://doi.org/10.1007/978-3-030-36126-6\_{}35.

Přehled o publikaci