An Automatic Extraction Tool for Ethnic Vietnamese Thai Dances Concepts

Autor: Truong-Thanh Ma, Karim Tabia, Zied Bouraoui, Salem Benferhat, Thanh-Nghi Do, Nguyen-Khang Pham
Přispěvatelé: Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), College of Information and Communication Technology (CICT), Can Tho University [Vietnam] (CTU), Multimedia content-based indexing (TEXMEX), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: ICMLA 2019-18th IEEE International Conference On Machine Learning And Applications
ICMLA 2019-18th IEEE International Conference On Machine Learning And Applications, Dec 2019, Boca Raton, Florida, United States. pp.1527-1530, ⟨10.1109/ICMLA.2019.00252⟩
2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)
ICMLA
Popis: International audience; In recent year, preservation and promotion of the ICHs are one of the problems of interest. In this paper, we focus on modelling the traditional dance domain, particularly modelling traditional Vietnamese dances. To conserve significant characteristics of dances, we proposed an ontology to represent the significant movements features of Ethnic Vietnamese Thai Dances (EVTDs). Particularly, a detailed description of the movement schemas of EVTDs is presented in this paper. Additionally, we present how to build an automatic extraction tool to collect the fundamental movements data of EVTDs using machine learning. Finally, we represented explicitly how to store those extracted features from raw dance videos into prioritized Ontology-based proposed.
Databáze: OpenAIRE