Revealing the Characteristics of Balinese Dance Maestros by Analyzing Silhouette Sequence Patterns Using Bag of Visual Movement with HoG and SIFT Features

Authors

  • Made Windu Antara Kesiman Universitas Pendidikan Ganesha
  • I Made Dendi Maysanjaya Universitas Pendidikan Ganesha
  • I Made Ardwi Pradnyana Universitas Pendidikan Ganesha
  • I Made Gede Sunarya Universitas Pendidikan Ganesha
  • Putu Hendra Suputra Universitas Pendidikan Ganesha

DOI:

https://doi.org/10.5614/itbj.ict.res.appl.2021.15.1.6

Keywords:

Balinese dance, feature, movement, pattern, sequence

Abstract

The aim of this research was to reveal and explore the characteristics of Balinese dance maestros by analyzing silhouette sequence patterns of Balinese dance movements. A method and complete scheme for the extraction and construction of silhouette features of Balinese dance movements are proposed to enable performing quantitative analysis of Balinese dance movement patterns. Two different feature extraction methods, namely the Histogram of Gradient (HoG) feature and the Scale Invariant Features Transform (SIFT) descriptor, were used to build the final feature, called the Bag of Visual Movement (BoVM) feature. This research also makes a technical contribution with the proposal of quantifying measures to analyze the movement patterns of Balinese dances and to create the profile and characteristics of dance maestros/creators. Eight Balinese dances from three different Balinese dance maestros were analyzed in this work. Based on the experimental results, the proposed method was able to visually detect and extract patterns from silhouette sequences of Balinese dance movements. Quantitatively, the pattern measures for profiling of Balinese dances and maestros revealed a number of significant characteristics of different dances and different maestros.

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References

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Published

2021-07-06

How to Cite

Kesiman, M. W. A., Maysanjaya, I. M. D., Pradnyana, I. M. A., Sunarya, I. M. G., & Suputra, P. H. (2021). Revealing the Characteristics of Balinese Dance Maestros by Analyzing Silhouette Sequence Patterns Using Bag of Visual Movement with HoG and SIFT Features. Journal of ICT Research and Applications, 15(1), 89-104. https://doi.org/10.5614/itbj.ict.res.appl.2021.15.1.6

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