Embodied Co-Creation with Real-Time Generative AI: An Ukiyo-E Interactive Art Installation

Generative artificial intelligence (AI) is reshaping creative practices, yet many systems rely on traditional interfaces, limiting intuitive and embodied engagement. This study presents a qualitative observational analysis of participant interactions with a real-time generative AI installation designed to co-create Ukiyo-e-style artwork through embodied inputs. The system dynamically interprets physical presence, object manipulation, body poses, and gestures to influence AI-generated visuals displayed on a large public screen. Drawing on systematic video analysis and detailed interaction logs across 13 sessions, the research identifies core modalities of interaction, patterns of co-creation, and user responses. Tangible objects with salient visual features such as color and pattern emerged as the primary, most intuitive input method, while bodily poses and hand gestures served as compositional modifiers. The system’s immediate feedback loop enabled rapid learning and iterative exploration and enhanced the user’s feeling of control. Users engaged in collaborative discovery, turn-taking, and shared authorship, frequently expressing a positive effect. The findings highlight how embodied interaction lowers cognitive barriers, enhances engagement, and supports meaningful human–AI collaboration. This study offers design implications for future creative AI systems, emphasizing accessibility, playful exploration, and cultural resonance, with the potential to democratize artistic expression and foster deeper public engagement with digital cultural heritage.

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Publication Details

Journal
Digital
Published
2025-11-07
DOI
https://doi.org/10.3390/digital5040061
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
0.00

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article

Embodied Co-Creation with Real-Time Generative AI: An Ukiyo-E Interactive Art Installation

Juan Carlos Chacón, Ming-Shin Lu, Hisa Martínez Nimi
Digital
Virtual Reality Applications and Impacts
article

Embodied Co-Creation with Real-Time Generative AI: An Ukiyo-E Interactive Art Installation

Juan Carlos Chacón, Ming-Shin Lu, Hisa Martínez Nimi
article en

Abstract

Generative artificial intelligence (AI) is reshaping creative practices, yet many systems rely on traditional interfaces, limiting intuitive and embodied engagement. This study presents a qualitative observational analysis of participant interactions with a real-time generative AI installation designed to co-create Ukiyo-e-style artwork through embodied inputs. The system dynamically interprets physical presence, object manipulation, body poses, and gestures to influence AI-generated visuals displayed on a large public screen. Drawing on systematic video analysis and detailed interaction logs across 13 sessions, the research identifies core modalities of interaction, patterns of co-creation, and user responses. Tangible objects with salient visual features such as color and pattern emerged as the primary, most intuitive input method, while bodily poses and hand gestures served as compositional modifiers. The system’s immediate feedback loop enabled rapid learning and iterative exploration and enhanced the user’s feeling of control. Users engaged in collaborative discovery, turn-taking, and shared authorship, frequently expressing a positive effect. The findings highlight how embodied interaction lowers cognitive barriers, enhances engagement, and supports meaningful human–AI collaboration. This study offers design implications for future creative AI systems, emphasizing accessibility, playful exploration, and cultural resonance, with the potential to democratize artistic expression and foster deeper public engagement with digital cultural heritage.

DigitalVol. 5(4)
Chiba University (JP)
Chiba University
Openalex Percentile: Top 66%
Virtual Reality Applications and Impacts
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Embodied Co-Creation with Real-Time Generative AI: An Ukiyo-E Interactive Art Installation — Juan Carlos Chacón, Ming-Shin Lu, et al. · Digital (2025) | TGRS Research Map | TGRS