Visual noise mask for human point-light displays: A coding-free approach

Detalhes bibliográficos
Autor(a) principal: Senra, Catarina Carvalho
Data de Publicação: 2025
Outros Autores: Sampaio, Adriana, Lapenta, Olivia Morgan
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://hdl.handle.net/1822/94393
Resumo: Human point-light displays consist of luminous dots representing human articulations, thus depicting actions without pictorial information. These stimuli are widely used in action recognition experiments. Because humans excel in decoding human motion, point-light displays (PLDs) are often masked with additional moving dots (noise masks), thereby challenging stimulus recognition. These noise masks are typically found within proprietary programming software, entail file format restrictions, and demand extensive programming skills. To address these limitations, we present the first user-friendly stepby-step guide to develop visual noise to mask PLDs using free, open-source software that offers compatibility with various file formats, features a graphical interface, and facilitates the manipulation of both 2D and 3D videos. Further, to validate our approach, we tested two generated masks in a pilot experiment with 12 subjects and demonstrated that they effectively jeopardised human agent recognition and, therefore, action visibility. In sum, the main advantages of the presented methodology are its cost-effectiveness and ease of use, making it appealing to novices in programming. This advancement holds the potential to stimulate young researchers’ use of PLDs, fostering further exploration and understanding of human motion perception.
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spelling Visual noise mask for human point-light displays: A coding-free approachPoint-light walkersVisual noiseAction perceptionBlender softwareHuman point-light displays consist of luminous dots representing human articulations, thus depicting actions without pictorial information. These stimuli are widely used in action recognition experiments. Because humans excel in decoding human motion, point-light displays (PLDs) are often masked with additional moving dots (noise masks), thereby challenging stimulus recognition. These noise masks are typically found within proprietary programming software, entail file format restrictions, and demand extensive programming skills. To address these limitations, we present the first user-friendly stepby-step guide to develop visual noise to mask PLDs using free, open-source software that offers compatibility with various file formats, features a graphical interface, and facilitates the manipulation of both 2D and 3D videos. Further, to validate our approach, we tested two generated masks in a pilot experiment with 12 subjects and demonstrated that they effectively jeopardised human agent recognition and, therefore, action visibility. In sum, the main advantages of the presented methodology are its cost-effectiveness and ease of use, making it appealing to novices in programming. This advancement holds the potential to stimulate young researchers’ use of PLDs, fostering further exploration and understanding of human motion perception.Olivia M. Lapenta is supported by the Psychology Research Centre [PSI/01662], School of Psychology, University of Minho, and by the Portuguese Foundation for Science and Technology through the Portuguese State Budget [UIDB/PSI/01662/2020] [SFRH/BPD/72710/2010]. Adriana C. S. Sampaio is supported by the Psychology Research Centre, School of Psychology, University of Minho, and by the Portuguese Foundation for Science and Technology through the Portuguese State Budget [UIDB/PSI/01662/2020].MDPIUniversidade do MinhoSenra, Catarina CarvalhoSampaio, AdrianaLapenta, Olivia Morgan2025-012025-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/94393engSenra, C. C., Sampaio, A. C. S., & Lapenta, O. M. (2025, January 2). Visual Noise Mask for Human Point-Light Displays: A Coding-Free Approach. NeuroSci. MDPI AG. http://doi.org/10.3390/neurosci601000210.3390/neurosci6010002info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-15T01:17:24Zoai:repositorium.sdum.uminho.pt:1822/94393Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:39:43.507333Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Visual noise mask for human point-light displays: A coding-free approach
title Visual noise mask for human point-light displays: A coding-free approach
spellingShingle Visual noise mask for human point-light displays: A coding-free approach
Senra, Catarina Carvalho
Point-light walkers
Visual noise
Action perception
Blender software
title_short Visual noise mask for human point-light displays: A coding-free approach
title_full Visual noise mask for human point-light displays: A coding-free approach
title_fullStr Visual noise mask for human point-light displays: A coding-free approach
title_full_unstemmed Visual noise mask for human point-light displays: A coding-free approach
title_sort Visual noise mask for human point-light displays: A coding-free approach
author Senra, Catarina Carvalho
author_facet Senra, Catarina Carvalho
Sampaio, Adriana
Lapenta, Olivia Morgan
author_role author
author2 Sampaio, Adriana
Lapenta, Olivia Morgan
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Senra, Catarina Carvalho
Sampaio, Adriana
Lapenta, Olivia Morgan
dc.subject.por.fl_str_mv Point-light walkers
Visual noise
Action perception
Blender software
topic Point-light walkers
Visual noise
Action perception
Blender software
description Human point-light displays consist of luminous dots representing human articulations, thus depicting actions without pictorial information. These stimuli are widely used in action recognition experiments. Because humans excel in decoding human motion, point-light displays (PLDs) are often masked with additional moving dots (noise masks), thereby challenging stimulus recognition. These noise masks are typically found within proprietary programming software, entail file format restrictions, and demand extensive programming skills. To address these limitations, we present the first user-friendly stepby-step guide to develop visual noise to mask PLDs using free, open-source software that offers compatibility with various file formats, features a graphical interface, and facilitates the manipulation of both 2D and 3D videos. Further, to validate our approach, we tested two generated masks in a pilot experiment with 12 subjects and demonstrated that they effectively jeopardised human agent recognition and, therefore, action visibility. In sum, the main advantages of the presented methodology are its cost-effectiveness and ease of use, making it appealing to novices in programming. This advancement holds the potential to stimulate young researchers’ use of PLDs, fostering further exploration and understanding of human motion perception.
publishDate 2025
dc.date.none.fl_str_mv 2025-01
2025-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/94393
url https://hdl.handle.net/1822/94393
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Senra, C. C., Sampaio, A. C. S., & Lapenta, O. M. (2025, January 2). Visual Noise Mask for Human Point-Light Displays: A Coding-Free Approach. NeuroSci. MDPI AG. http://doi.org/10.3390/neurosci6010002
10.3390/neurosci6010002
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
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instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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