TY - CONF
KW - Deep learning
KW - Artificial intelligence
KW - Applications
KW - Folk dance preservation
KW - Human motion analysis from video
AU - N. Grammalidis
AU - I. Kico
AU - F. Liarokapis
AB - 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.
BT - International Conference on Strategic Innovative Marketing and Tourism, ICSIMAT 2019
C3 - Springer Proc. Bus. Econ.
DA - 2020///
DB - Scopus
DO - 10.1007/978-3-030-36126-6_35
LA - English
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.
PB - Springer Science and Business Media B.V.
PY - 2020
SN - 21987246 (ISSN); 9783030361259 (ISBN)
SP - 321
EP - 329
EP - 
T2 - International Conference on Strategic Innovative Marketing and Tourism, ICSIMAT 2019
TI - Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126113393&doi=10.1007%2f978-3-030-36126-6_35&partnerID=40&md5=8734a7db3ec0534f60f17f09de857137
Y2 - 2019/07/17/
ER -