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

In: Strategic Innovative Marketing and Tourism

Author

Listed:
  • Nikos Grammalidis

    (Information Technologies Institute, CERTH)

  • Iris Kico

    (Masaryk University)

  • Fotis Liarokapis

    (Masaryk University)

Abstract

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.

Suggested Citation

  • Nikos Grammalidis & Iris Kico & Fotis Liarokapis, 2020. "Analysis of Human Motion Based on AI Technologies: Applications for Safeguarding Folk Dance Performances," Springer Proceedings in Business and Economics, in: Androniki Kavoura & Efstathios Kefallonitis & Prokopios Theodoridis (ed.), Strategic Innovative Marketing and Tourism, pages 321-329, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-36126-6_35
    DOI: 10.1007/978-3-030-36126-6_35
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