LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance

José Siopa; Rui Filipe Antunes; Cecília De Lima; João Carrilho; Ana Paula Cláudio; Maria Beatriz Carmo

doi:10.1145/3658852.3659081

LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance

José Siopa, Rui Filipe Antunes, Cecília De Lima, João Carrilho, Ana Paula Cláudio, Maria Beatriz Carmo

CICANT - Centre for Research in Applied Communication, Culture, and New Technologies

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Ghostdance is an evolving generative art project in the field of dance and virtual reality (VR). It mixes visual, auditory and immersive experiences, making use of generative algorithms to create a dynamic audiovisual landscape with continuously changing images and sounds. The performance consists of three interconnected components: a) a duet featuring a human dancer and an avatar mirroring the movements of an absent person; b) the transformation of the physical movements of the human dancer into a visualization of a hybrid body, constantly redefined as a swarm of virtual entities; and c) the sonification of the dancer's movements, introducing an auditory dimension to the exploration of movement. Performers dance in duets with virtual bodies, with pre-choreographed movements, in a visual and auditory landscape that evolves in real time due to adaptive generative algorithms responding to the presence and movements of the performer, informed by pretrained machine learning algorithms able to categorize the quality of the dancer's movement in Laban terms.

Original language	English
Title of host publication	Proceedings of the 9th International Conference on Movement and Computing
Subtitle of host publication	MOCO 2024 Beyond Control
Publisher	Association for Computing Machinery
Number of pages	5
ISBN (Electronic)	9798400709944
DOIs	https://doi.org/10.1145/3658852.3659081
Publication status	Published - 30 May 2024
Event	9th International Conference on Movement and Computing, MOCO 2024 Beyond Control - Utrecht, Netherlands Duration: 30 May 2024 → 2 Jun 2024

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	9th International Conference on Movement and Computing, MOCO 2024 Beyond Control
Country/Territory	Netherlands
City	Utrecht
Period	30/05/24 → 2/06/24

Bibliographical note

Publisher Copyright:
© 2024 Owner/Author.

Funding

This work was supported by FCT through project GhostDance: A Methodology to analyse dance movement in interaction with virtual reality, ref: FCT:EXPL/ART-PER/1238/2021; and FilmEU - European Universities Alliance for Film and Media Arts and supported in part by funding from FILMEU-RIT - Research | Innovation | Transformation project, European Union GRANT-NUMBER: H2020-IBA-SwafS Support-2-2020, Ref: 101035820, from FilmEU - The European University for Film and Media Arts project, European Union GRANT-NUMBER: 101004047, EPP-EUR-UNIV-2020. The written work was proofread by language model ChatGPT-3.5, an AI language model developed by OpenAI.

Funders	Funder number
European Universities Alliance for Film and Media Arts
FILMEU-RIT
FilmEU
Fundação para a Ciência e a Tecnologia	EXPL/ART-PER/1238/2021
European Commission	101035820
European University for Film and Media Arts project	EPP-EUR-UNIV-2020, 101004047

Keywords

COMMUNICATION
DANCE
AUDIOVISUAL
PERFORMANCE
VIRTUAL REALITY

Access to Document

10.1145/3658852.3659081

Cite this

Siopa, J., Antunes, R. F., De Lima, C., Carrilho, J., Cláudio, A. P., & Carmo, M. B. (2024). LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance. In Proceedings of the 9th International Conference on Movement and Computing: MOCO 2024 Beyond Control Article 28 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3658852.3659081

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title = "LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance",

abstract = "Ghostdance is an evolving generative art project in the field of dance and virtual reality (VR). It mixes visual, auditory and immersive experiences, making use of generative algorithms to create a dynamic audiovisual landscape with continuously changing images and sounds. The performance consists of three interconnected components: a) a duet featuring a human dancer and an avatar mirroring the movements of an absent person; b) the transformation of the physical movements of the human dancer into a visualization of a hybrid body, constantly redefined as a swarm of virtual entities; and c) the sonification of the dancer's movements, introducing an auditory dimension to the exploration of movement. Performers dance in duets with virtual bodies, with pre-choreographed movements, in a visual and auditory landscape that evolves in real time due to adaptive generative algorithms responding to the presence and movements of the performer, informed by pretrained machine learning algorithms able to categorize the quality of the dancer's movement in Laban terms.",

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author = "Jos{\'e} Siopa and Antunes, {Rui Filipe} and {De Lima}, Cec{\'i}lia and Jo{\~a}o Carrilho and Cl{\'a}udio, {Ana Paula} and Carmo, {Maria Beatriz}",

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year = "2024",

month = may,

day = "30",

doi = "10.1145/3658852.3659081",

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Siopa, J, Antunes, RF, De Lima, C, Carrilho, J, Cláudio, AP & Carmo, MB 2024, LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance. in Proceedings of the 9th International Conference on Movement and Computing: MOCO 2024 Beyond Control., 28, ACM International Conference Proceeding Series, Association for Computing Machinery, 9th International Conference on Movement and Computing, MOCO 2024 Beyond Control, Utrecht, Netherlands, 30/05/24. https://doi.org/10.1145/3658852.3659081

LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance. / Siopa, José; Antunes, Rui Filipe; De Lima, Cecília et al.
Proceedings of the 9th International Conference on Movement and Computing: MOCO 2024 Beyond Control. Association for Computing Machinery, 2024. 28 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Ghostdance is an evolving generative art project in the field of dance and virtual reality (VR). It mixes visual, auditory and immersive experiences, making use of generative algorithms to create a dynamic audiovisual landscape with continuously changing images and sounds. The performance consists of three interconnected components: a) a duet featuring a human dancer and an avatar mirroring the movements of an absent person; b) the transformation of the physical movements of the human dancer into a visualization of a hybrid body, constantly redefined as a swarm of virtual entities; and c) the sonification of the dancer's movements, introducing an auditory dimension to the exploration of movement. Performers dance in duets with virtual bodies, with pre-choreographed movements, in a visual and auditory landscape that evolves in real time due to adaptive generative algorithms responding to the presence and movements of the performer, informed by pretrained machine learning algorithms able to categorize the quality of the dancer's movement in Laban terms.

KW - COMMUNICATION

KW - DANCE

KW - AUDIOVISUAL

KW - PERFORMANCE

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KW - DANÇA

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T3 - ACM International Conference Proceeding Series

BT - Proceedings of the 9th International Conference on Movement and Computing

PB - Association for Computing Machinery

Y2 - 30 May 2024 through 2 June 2024

ER -

Siopa J, Antunes RF, De Lima C, Carrilho J, Cláudio AP, Carmo MB. LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance. In Proceedings of the 9th International Conference on Movement and Computing: MOCO 2024 Beyond Control. Association for Computing Machinery. 2024. 28. (ACM International Conference Proceeding Series). doi: 10.1145/3658852.3659081

LMA driven Dynamic Audiovisuals in a Virtual Reality Live Dance Performance: Ghostdance

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

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