Automatic Sign Dance Synthesis from Gesture-based Sign Language

Iwamoto, Naoya, Shum, Hubert, Asahina, Wakana and Morishima, Shigeo (2019) Automatic Sign Dance Synthesis from Gesture-based Sign Language. In: Motion, Interaction and Games (MIG ’19): October 28–30, 2019, Newcastle upon Tyne, United Kingdom ; proceedings. ACM, New York, USA, pp. 1-9. ISBN 9781450369947

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Official URL: https://doi.org/10.1145/3359566.3360069

Abstract

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.

Item Type: Book Section
Additional Information: © ACM 2019. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Motion, Interaction and Games (MIG ’19), October 28–30, 2019, Newcastle upon Tyne, United Kingdom. ACM, New York, NY, USA, https://doi.org/10.1145/3359566.3360069.
Uncontrolled Keywords: Motion Synthesis, Dance, Sign Language, Multiple Regression Analysis
Subjects: G400 Computer Science
G500 Information Systems
G700 Artificial Intelligence
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 17 Sep 2019 08:16
Last Modified: 20 May 2020 11:15
URI: http://nrl.northumbria.ac.uk/id/eprint/40707

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