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Sarawak Traditional Dance Motion Analysis and Comparison using Microsoft Kinect V2

by Michael-Lian Gau 1 , Huong Yong Ting 1 , Jackie Tiew-Wei Ting 1 , Marcella Peter 1 , Khairunnisa Ibrahim 2
1 Drone Research and Application Centre, School of Computing and Creative Media, University of Technology Sarawak, No. 1, Jalan Universiti, 96000 Sibu, Sarawak
2 Advanced Centre for Sustainable Socio-Economic and Technological Development, School of Computing and Creative Media, University of Technology Sarawak, No. 1, Jalan Universiti, 96000 Sibu, Sarawak

SUBMITTED: 24 March 2022; ACCEPTED: 12 April 2022; PUBLISHED: 17 April 2022

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Green Intell. Syst. Appl. 2022, 2 (1), 42-52
https://doi.org/10.53623/gisa.v2i1.78
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Abstract

Abstract
This research project aimed to develop a software program or an interactive dance motion analysis application that utilizes modern technology to preserve and maintain the Sarawak traditional dance culture. The software program employs the Microsoft Kinect V2 to collect the digital dance data. The proposed method analyses the collected dance data for comparison purposes only. The comparison process was executed by displaying a traditional dance on the screen where the user who wants to learn the traditional dance can follow it and obtain results on how similar the dance is compared to the recorded dance data. The comparison of the performed and recorded dance data was visualized in graph form. The comparison graph showed that the Microsoft Kinect V2 sensors were capable of comparing the dance motion but with minor glitches in detecting the joint orientation. Using better depth sensors would make the comparison more accurate and less likely to have problems with figuring out how the joints move.
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Keywords: Microsoft Kinect; Sarawak Dance; Motion Analysis; Motion Comparison

Creative Commons Attribution 4.0 International (CC BY 4.0) License
© 2022 Michael-Lian Gau, Huong Yong Ting, Jackie Tiew-Wei Ting, Marcella Peter, Khairunnisa Ibrahim. This is an open access article distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Gau, M.-L., Ting, H. Y., Ting, J. T.-W., Peter, M., & Ibrahim, K. (2022). Sarawak Traditional Dance Motion Analysis and Comparison using Microsoft Kinect V2. Green Intelligent Systems and Applications, 2(1), 42–52. https://doi.org/10.53623/gisa.v2i1.78
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