Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Digitizing traditional dances under extreme clothing

The case study of Eyo

Bibliographic Data

ID12513121
AuthorsTemi Ami-Williams (Université Clermont Auvergne), Christina-Georgia Serghides (0009-0007-1409-6567, University of Cyprus), Andreas Aristidou (0000-0001-7754-0791, University of Cyprus, corresponding author)
Year2024
Volume67
Pages145-157
Publication date2024-03-08
Open AccessYes
TypeARTICLE
VenueJournal of Cultural Heritage (JOURNAL)
Journal identifiersISSN: 1296-2074 • E-ISSN: 1778-3674
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.culher.2024.02.011
OpenAlexW4392611014
LanguageEN
Citations received1
References cited43

Research Focus: Importance of merging traditional clothing and precise movements in dance digitization. • Technology Evaluation: In-depth review of mocap technologies for accurate dance capture. • Efficient Digitization Pipeline: Streamlined process for digitizing folk dances with "extreme clothing." • Comparative Analysis & Impact Assessment: Evaluation of mocap devices' performance with and without traditional costumes. • Virtual Reality (VR) Exploration: Study on how traditional attire affects user experience in VR. This work studies the challenges associated with capturing the movement of dance performers wearing traditional African masquerade garments, specifically focusing on the Eyo masquerade dance, a cultural heritage creation from Lagos, Nigeria, and discusses the crucial role the costume has in enhancing the overall performance. The work particularly investigates the capabilities and limitations of current motion capture technology in effectively capturing the movements of both the dancer and the costume, especially when the performer wears what we refer to as “extreme clothing”, such as full body costumes or heavy garments. To overcome these challenges, we employ a combination of motion capture technologies to precisely capture the movements of the performer both with and without the costume, while assessing their respective advantages and limitations. Furthermore, we analyze the disparities in motion quality between these two scenarios to comprehend the influence of the costume on the overall performance. This research has led to the development of an efficient pipeline for digitizing and visualizing folk dances featuring intricate and bulky costumes. The findings of this study offer invaluable insights into the application of motion capture technology for acquiring the movements of performers, including the deformation of their costumes, in cultural heritage dances. As a final outcome of this work, we present a visually captivating animation showcasing an Eyo masquerade dance performance, underscoring the potential of motion capture technology as a tool for preserving and promoting cultural heritage dances

Aesthetics · Animation · Art · Clothing · Costume design · Cultural heritage · Dance · Motion (physics · Motion Capture · Movement (music · Performing arts · Visual arts · Computer Science · History · Human Motion and Animation · Human Pose and Action Recognition · Video Analysis and Summarization · Artificial Intelligence

  • Enhancing creative learning in Thai classical dance education

    Open Access•Napatprapa Pathrapoowanun, Parama Kwangmuang et al.•Digital Applications in…•2025

  • Violin Plots

    Jerry L Hintze, Ray D Nelson•The American Statistician•1998

  • OpenPose

    Open Access•Zhe Cao, Gines Hidalgo et al.•IEEE Transactions on Pattern…•2021

  • A Nonverbal Language for Imagining and Learning

    Open Access•Judith Lynne Hanna•Educational Researcher•2008

  • Documentation of cultural heritage using digital photogrammetry and laser scanning

    Open Access•Naci Yastikli•Journal of Cultural Heritage•2007

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae