Automatic sign dance synthesis from gesture-based sign language

Naoya Iwamoto, Hubert P.H. Shum, Wakana Asahina, Shigeo Morishima

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Automatic dance synthesis has become more and more popular due to the increasing demand in computer games and animations. Existing research generates dance motions without much consideration for the context of the music. In reality, professional dancers make choreography according to the lyrics and music features. In this research, we focus on a particular genre of dance known as sign dance, which combines gesture-based sign language with full body dance motion. We propose a system to automatically generate sign dance from a piece of music and its corresponding sign gesture. The core of the system is a Sign Dance Model trained by multiple regression analysis to represent the correlations between sign dance and sign gesture/music, as well as a set of objective functions to evaluate the quality of the sign dance. Our system can be applied to music visualization, allowing people with hearing difficulties to understand and enjoy music.

Original languageEnglish
Title of host publicationProceedings - MIG 2019
Subtitle of host publicationACM Conference on Motion, Interaction, and Games
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450369947
Publication statusPublished - 2019 Oct 28
Event2019 ACM Conference on Motion, Interaction, and Games, MIG 2019 - Newcastle upon Tyne, United Kingdom
Duration: 2019 Oct 282019 Oct 30

Publication series

NameProceedings - MIG 2019: ACM Conference on Motion, Interaction, and Games


Conference2019 ACM Conference on Motion, Interaction, and Games, MIG 2019
Country/TerritoryUnited Kingdom
CityNewcastle upon Tyne


  • Dance
  • Motion Synthesis
  • Multiple Regression Analysis
  • Sign Language

ASJC Scopus subject areas

  • Computer Science Applications
  • Human-Computer Interaction
  • Education


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