Abstract: Folk dance (FD) is a type of traditional dance that has been handed down through a culture or group from generation to generation. It is crucial to preserve and safeguard this type of cultural legacy since it can reflect the history and identity of particular nations. However, due to ineffective preservation and conservation techniques, the survival of FDs is being negatively impacted more and more. Its extinction may be caused by ignorance about and disregard for preservation and conservation efforts. The most efficient method for digitizing intangible cultural property, including FDs, is motion capture (MoCap). MoCap enables the conversion of real-time movement into digital performance to produce motion templates. This paper aims to provide suggestions and guidelines in conducting research to generate motion templates of FDs. Several key approaches are presented and discussed in detail, including acquaintance meetings, procedures and approval, interviews and experiments, and the framework. The proposed framework includes models for MoCap, skeleton generation, skeleton refinement, and evaluation. By implementing the proposed framework, the motion templates for FDs can be created. The generated motion templates will preserve and conserve FDs and guarantee their originality and authenticity.

Amir Irfan Mazian, Wan Rizhan, Normala Rahim, Azrul Amri Jamal, Ismahafezi Ismail and Syed Abdullah Fadzli, “A Theoretical Framework for Creating Folk Dance Motion Templates using Motion Capture” International Journal of Advanced Computer Science and Applications(IJACSA), 14(5), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140547

@article{Mazian2023,
title = {A Theoretical Framework for Creating Folk Dance Motion Templates using Motion Capture},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140547},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140547},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Amir Irfan Mazian and Wan Rizhan and Normala Rahim and Azrul Amri Jamal and Ismahafezi Ismail and Syed Abdullah Fadzli}
}