[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118022-en":3,"doc-seo-118022-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118022,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Exploring the impact of machine learning on dance performance - a systematic review","Machine learning and dance form an increasingly studied intersection, using techniques such as human-pose detection to analyze movement and produce real-time visual models. Despite expanding interest, prior work has not comprehensively evaluated machine learning’s effects on dance across multiple dimensions. This systematic review examines impacts on choreographic creation support, dataset/network collection and training, improved human-pose detection methods, and perception with new visual representations. Results show both artistic benefits and ethical concerns around ownership and authorship, highlighting priorities for further research.","Please cite the Published Version  \nNogueira, Maria Rita , Menezes, Paulo and Maçãs de Carvalho, José (2024) Exploring the impact of machine learning on dance performance: a systematic review. International Journal of Performance Arts and Digital Media. pp. 1-50. ISSN 1479-4713  \nDOI: [https://doi.org/10.1080/14794713.2024.2338927](https://doi.org/10.1080/14794713.2024.2338927)  \nPublisher: Taylor & Francis  \nVersion: Published Version  \nDownloaded from: [https://e-space.mmu.ac.uk/634544/](https://e-space.mmu.ac.uk/634544/)  \nUsage rights:  Creative Commons: Attribution 4 .0  \nAdditional Information: This is an open access article which first appeared in International Journal of Performance Arts and Digital Media  \nEnquiries:  \nIf you have questions about this document, contact [openresearch@mmu.ac.uk. Please](openresearch@mmu.ac.uk. Please) include the URL of the record in e-space. If you believe that your, or a third party's rights have been compromised through this document please see our Take Down policy (available from [https://www.mmu.ac.uk/library/using-the-library/policies-and-guidelines](https://www.mmu.ac.uk/library/using-the-library/policies-and-guidelines))  \nInternational Journal of Performance Arts and Media  \nDigital  \nISSN: (Print) (Online) Journal [homepage: ](homepage: www.tandfonline.com/journals/rpdm20)[www.tandfonline.com/journals/rpdm20](homepage: www.tandfonline.com/journals/rpdm20)  \nExploring the impact of machine learning on dance performance: a systematic review  \nMaria Rita Nogueira, Paulo Menezes & José Maçãs de Carvalho  \nTo cite this article: Maria Rita Nogueira, Paulo Menezes & José Maçãs de Carvalho (24 Apr 2024): Exploring the impact of machine learning on dance performance: a systematic review, International Journal of Performance Arts and Digital Media, DOI: 10. 1080/14794713 .2024.2338927  \nTo link to this article: [https://doi.org/10.1080/14794713.2024.2338927](https://doi.org/10.1080/14794713.2024.2338927)  \n© 2024 The Author(s) . Published by Informa UK Limited, trading as Taylor & Francis Group  \n\n|  Published online: 24 Apr 2024. |\n| --- |\n|  Submit your article to this journal  |\n|  Article views: 89 |\n|  View related articles  |\n|  View Crossmark data |\n\nFull Terms & Conditions of access and use can be found at [https://www.tandfonline.com/action/journalInformation?journalCode=rpdm20](https://www.tandfonline.com/action/journalInformation?journalCode=rpdm20)  \nINTERNATIONAL JOURNAL OF PERFORMANCE ARTS AND DIGITAL MEDIA [https://doi.org/10.1080/14794713.2024.2338927](https://doi.org/10.1080/14794713.2024.2338927)  \nExploring the impact of machine learning on dance performance: a systematic review  \nMaria Rita Nogueira a,b, Paulo Menezesb,c and José Maçãs de Carvalhod  \naSchool of Digital Arts, Manchester Metropolitan University, Manchester, UK; bInstitute of Systems and Robotics, University of Coimbra, Coimbra, Portugal; cDepartment of Electrical and Computer Engineering, University of Coimbra, Coimbra, Portugal; dCentre for Interdisciplinary Studies, University of Coimbra,  \nCoimbra, Portugal  \nABSTRACT  \nIn recent years, the intersection of machine learning and dance has garnered increasing attention as a means to enhance the aestheticsand creativity of dance performance. Machine learning techniques, such as human-pose detection, have been utilized to analyze body movement and generate visual models in realtime, offering new approaches to traditional art form. However, despite the growing interest in this field, there is a lack of comprehensive research that evaluates the impact of machine learning on dance from multiple perspectives. This systematic review addresses this gap by examining the impact of machine learning on four key aspects of dance performance: choreographic creation support; dataset or network collection and training; improved techniques of humanpose detection; perception and new visual representations of dance movement. This exploration reveals that machine learning co","cbCaijr2PCqapnGO","https://ap.wps.com/l/cbCaijr2PCqapnGO","pdf",3777113,1,52,"English","en",105,"# Introduction\n# Abstract\n# Keywords\n# Article history","[{\"question\":\"What gap does the systematic review address about machine learning in dance?\",\"answer\":\"It addresses the lack of comprehensive research evaluating machine learning’s impact on dance from multiple perspectives.\"},{\"question\":\"Which four aspects of dance performance does the review focus on?\",\"answer\":\"Choreographic creation support; dataset or network collection and training; improved human-pose detection techniques; and perception with new visual representations of dance movement.\"},{\"question\":\"What are the main outcomes regarding machine learning’s effect on artistic practice?\",\"answer\":\"Machine learning can contribute positively by adding novelty and increasing audience interest, while also raising ethical concerns about artistic ownership and authorship.\"}]","Exploring the impact of machine learning on dance performance - a systematic review | PDF",1785680788,131,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"exploring-the-impact-of-machine-learning-on-dance-performance-a-systematic-review","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/exploring-the-impact-of-machine-learning-on-dance-performance-a-systematic-review/118022/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What gap does the systematic review address about machine learning in dance?","Question",{"text":75,"@type":76},"It addresses the lack of comprehensive research evaluating machine learning’s impact on dance from multiple perspectives.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which four aspects of dance performance does the review focus on?",{"text":80,"@type":76},"Choreographic creation support; 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