Online Archive of University of Virginia Scholarship
Machine Learning Based Movement Comparison System for Dance Education; Uses, Impact, and Future of Artificial Intelligence in Dance7 views
Author
Menon, Gayathri, School of Engineering and Applied Science, University of Virginia
Advisors
Stone, Derrick, EN-Comp Science Dept, University of Virginia
Carrigan, Coleen, EN-Engineering and Society, University of Virginia
Abstract
Dance is an art form that is deeply rooted in human history, having existed for countless centuries, that has ties worldwide with culture, religion, health, and more. Artificial intelligence (abbreviated AI) is a broad category of technologies that is similarly impactful despite its novelty. It is being used in numerous fields, including artistic fields such as dance. Although AI was only recently introduced into the field of dance, the significance both hold in global society makes it crucial to assess the uses of AI in dance and the impact AI can have on dance. This research problem will be divided into two portions: a technical portion researching a particular use of AI, and an STS-based portion researching the impacts of AI. Both portions will be completed within a reduced scope, as the vast nature of dance makes studying it in its entirety difficult.
The technical aspect of this research works towards understanding the ways AI can be used in dance by creating a software program that utilizes movement detection technology, which is a type of AI technology, to assist dance students and teachers to learn and teach dance. This tool will take two submissions of photos and/or videos, one from a teacher and one from a learner performing the same movements. It will then use a movement detection framework to compare the movements and provide feedback for the learner. The goal of this technical project is to gain a deeper understanding of how AI can be used within the field of dance.
The STS-based research will assess impacts with the use of an STS framework on established dance forms, which are dance forms that developed over centuries and possess a set of rules and unique characteristics. The interactions between three dance-related AI models and two norms of established dances will be investigated to determine the current impacts of AI on dance as well as the ways AI should be used in dance moving forward to ensure positive impacts in the future. The goal of this STS-based research is to gain a more thorough understanding of how AI can impact dance in the present and the future. The research found that the current main uses of AI in dance is in education and choreography, with an overall positive impact provided that sufficient human supervision is present. It is then suggested for the future that AI technology should be used as a tool by members of the dance community with significant human involvement and supervision to encourage positive impacts and prevent harm.
Degree
BS (Bachelor of Science)
Keywords
Artificial Intelligence; Dance; Movement Detection; Machine Learning; MediaPipe
Notes
School of Engineering and Applied Science
Bachelor of Science in Computer Science
Technical Advisor: Derrick Stone
STS Advisor: Coleen Carrigan
Language
English
Rights
All rights reserved by the author (no additional license for public reuse)
Menon, Gayathri. Machine Learning Based Movement Comparison System for Dance Education; Uses, Impact, and Future of Artificial Intelligence in Dance. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2026-05-08, https://doi.org/10.18130/437b-qw58.