VJing을 위한 내러티브-타임라인 모델의 AI 확장 가능성 탐구
The purpose of this study is to develop a narrative-timeline framework for VJ practice that integrates artistic intention with technical execution. The model combines an eight-stage emotional narrative structure with a six-phase timeline workflow, positioning the VJ as both creative director and coordination mediator in live event production. Building on this foundation, the study explores how artificial intelligence can extend the framework through functions such as automated emotional tagging, predictive workflow optimization, and real-time conflict resolution. While still conceptual, the results indicate the design feasibility of a replicable blueprint for participatory and sustainable VJ practice. Future work will involve empirical validation and the development of AI-assisted tools that preserve human creative agency while expanding narrative and operational possibilities in live media performance.