Publicação

Motion capture for artists using AI apps

Ver documento

Detalhes bibliográficos
Resumo:Motion capture based on Artificial Intelligence (AI) represents a significant advancement in the capture and manipulation of human motion, providing a more accessible approach to generate lifelike animations. Traditionally, motion capture has been employed to produce realistic character movements for film and video games. However, its applications extend beyond figurative representation, enabling the mapping of motion onto diverse visual forms in various contexts, such as artistic installations and live performances. Traditional motion capture systems are costly, limiting accessibility for artists. AI-driven motion capture has democratized this technology, enabling innovative and abstract visual explorations. A key question arises: do AI-based motion capture tools produce meaningful results in diverse artistic contexts? This paper compares low-cost AI motion capture solutions, to evaluate their potential for artistic applications, through quantitative and qualitative analyses. Motion capture data from these AI solutions were used to generate abstract and non-representational visual interpretations.
Autores principais:Leite, Luis Barbosa
Assunto:Artificial intelligence Motion capture Performance animation Media arts
Ano:2025
País:Portugal
Tipo de documento:artigo
Tipo de acesso:unknown
Instituição associada:Universidade Católica Portuguesa
Idioma:inglês
Origem:Journal of Science and Technology of the Arts
_version_ 1863896969748938752
author Leite, Luis Barbosa
author_facet Leite, Luis Barbosa
author_role author
country_str PT
creators_json_str [{\"Person.name\":\"Leite, Luis Barbosa\"}]
datacite.creators.creator.creatorName.fl_str_mv Leite, Luis Barbosa
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Artificial intelligence
Motion capture
Performance animation
Media arts
datacite.titles.title.fl_str_mv Motion capture for artists using AI apps
dc.creator.none.fl_str_mv Leite, Luis Barbosa
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://doi.org/10.34632/jsta.2025.17630
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Universidade Católica Portuguesa
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.source.none.fl_str_mv Journal of Science and Technology of the Arts; Vol. 17 No. 1 (2025): Creative Digital Intelligence; 101-121
Journal of Science and Technology of the Arts; Vol. 17 N.º 1 (2025): Creative Digital Intelligence; 101-121
2183-0088
1646-9798
10.34632/jsta.2025.17.1
dc.subject.none.fl_str_mv Artificial intelligence
Motion capture
Performance animation
Media arts
dc.title.fl_str_mv Motion capture for artists using AI apps
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description Motion capture based on Artificial Intelligence (AI) represents a significant advancement in the capture and manipulation of human motion, providing a more accessible approach to generate lifelike animations. Traditionally, motion capture has been employed to produce realistic character movements for film and video games. However, its applications extend beyond figurative representation, enabling the mapping of motion onto diverse visual forms in various contexts, such as artistic installations and live performances. Traditional motion capture systems are costly, limiting accessibility for artists. AI-driven motion capture has democratized this technology, enabling innovative and abstract visual explorations. A key question arises: do AI-based motion capture tools produce meaningful results in diverse artistic contexts? This paper compares low-cost AI motion capture solutions, to evaluate their potential for artistic applications, through quantitative and qualitative analyses. Motion capture data from these AI solutions were used to generate abstract and non-representational visual interpretations.
dirty 0
eu_rights_str_mv unknown
format article
id citar_35bd6cd2d2f34e2c0ba4ecdd3bfe2d6e
identifier.doi.fl_str_mv https://doi.org/10.34632/jsta.2025.17630
instacron_str ucp
institution Universidade Católica Portuguesa
instname_str Universidade Católica Portuguesa
language eng
network_acronym_str citar
network_name_str Journal of Science and Technology of the Arts
oai_identifier_str oai:ojs.revistas.ucp.pt:article/17630
organization_str_mv urn:organizationAcronym:ucp
person_str_mv Leite, Luis Barbosa
publishDate 2025
publisher.none.fl_str_mv Universidade Católica Portuguesa
reponame_str Journal of Science and Technology of the Arts
repository_id_str urn:repositoryAcronym:citar
service_str_mv urn:repositoryAcronym:citar
spelling en-USMotion capture for artists using AI appsLeite, Luis BarbosaArtificial intelligenceMotion capturePerformance animationMedia artsCopyright (c) 2025 Luis Barbosa Leitehttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by/4.0https://doi.org/10.34632/jsta.2025.17630DOIhttps://revistas.ucp.pt/index.php/jsta/article/view/17630URLHasVersionhttps://revistas.ucp.pt/index.php/jsta/article/view/17630/17169URLHasVersionhttps://doi.org/10.34632/jsta.2025.17630DOI2025-07-29en-USMotion capture based on Artificial Intelligence (AI) represents a significant advancement in the capture and manipulation of human motion, providing a more accessible approach to generate lifelike animations. Traditionally, motion capture has been employed to produce realistic character movements for film and video games. However, its applications extend beyond figurative representation, enabling the mapping of motion onto diverse visual forms in various contexts, such as artistic installations and live performances. Traditional motion capture systems are costly, limiting accessibility for artists. AI-driven motion capture has democratized this technology, enabling innovative and abstract visual explorations. A key question arises: do AI-based motion capture tools produce meaningful results in diverse artistic contexts? This paper compares low-cost AI motion capture solutions, to evaluate their potential for artistic applications, through quantitative and qualitative analyses. Motion capture data from these AI solutions were used to generate abstract and non-representational visual interpretations.Universidade Católica Portuguesaapplication/pdfen-USJournal of Science and Technology of the Arts; Vol. 17 No. 1 (2025): Creative Digital Intelligence; 101-121pt-PTJournal of Science and Technology of the Arts; Vol. 17 N.º 1 (2025): Creative Digital Intelligence; 101-1212183-00881646-979810.34632/jsta.2025.17.1engjournal articlehttp://purl.org/coar/resource_type/c_6501literatureVoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85
spellingShingle Motion capture for artists using AI apps
Leite, Luis Barbosa
Artificial intelligence
Motion capture
Performance animation
Media arts
status_str VoR
subject.fl_str_mv Artificial intelligence
Motion capture
Performance animation
Media arts
title Motion capture for artists using AI apps
title_full Motion capture for artists using AI apps
title_fullStr Motion capture for artists using AI apps
title_full_unstemmed Motion capture for artists using AI apps
title_short Motion capture for artists using AI apps
title_sort Motion capture for artists using AI apps
topic Artificial intelligence
Motion capture
Performance animation
Media arts
topic_facet Artificial intelligence
Motion capture
Performance animation
Media arts
url https://doi.org/10.34632/jsta.2025.17630
visible 1