Glow with the Flow: AI-Assisted Creation of Ambient Lightscapes for Music Videos
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866912891183038464 |
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| author | Robinson, Frederic Anthony Raj, Vishnu Cooper, David Du, Fan Gunawan, David |
| author_facet | Robinson, Frederic Anthony Raj, Vishnu Cooper, David Du, Fan Gunawan, David |
| contents | Designed light is an established modality for live performance and music playback. Despite the growing availability of consumer smart lighting, the creation of designed light for music visualization remains limited to professional contexts due to time and skill constraints. To address this, we present an AI-assisted system for generating ambient light sequences for music videos. Informed by professional design heuristics, the system extracts salient features from source video and audio to generate an editable preliminary design of object based ambient light effect. We evaluated the system by comparing its autonomous output against hand-authored designs for three music videos. Findings from responses by 32 participants indicate that the initial output provides a viable baseline for further refinement by human authors. This work demonstrates the utility of AI-assisted workflows in supporting the creation and adoption of designed light beyond professional venues. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_08838 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Glow with the Flow: AI-Assisted Creation of Ambient Lightscapes for Music Videos Robinson, Frederic Anthony Raj, Vishnu Cooper, David Du, Fan Gunawan, David Human-Computer Interaction Designed light is an established modality for live performance and music playback. Despite the growing availability of consumer smart lighting, the creation of designed light for music visualization remains limited to professional contexts due to time and skill constraints. To address this, we present an AI-assisted system for generating ambient light sequences for music videos. Informed by professional design heuristics, the system extracts salient features from source video and audio to generate an editable preliminary design of object based ambient light effect. We evaluated the system by comparing its autonomous output against hand-authored designs for three music videos. Findings from responses by 32 participants indicate that the initial output provides a viable baseline for further refinement by human authors. This work demonstrates the utility of AI-assisted workflows in supporting the creation and adoption of designed light beyond professional venues. |
| title | Glow with the Flow: AI-Assisted Creation of Ambient Lightscapes for Music Videos |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.08838 |