Cinematic Pre-Visualization System: Automated 3D Scene Generation from Natural Language Descriptions Using NLP and JSON-Based Scene Representation
TL;DR
The Cinematic Pre-Visualization System is an end-to-end pipeline that converts natural language scene descriptions into structured three-dimensional previsualization scenes in Blender and Unity, offering a practical tool for the film, animation, and game production industries.
Abstract
The Cinematic Pre-Visualization System is an end-to-end pipeline that converts natural language scene descriptions into structured three-dimensional (3D) previsualization scenes in Blender and Unity. The system employs Natural Language Processing (NLP) techniques using the spaCy library to extract semantic scene elements including characters, objects, spatial relationships, lighting conditions, and camera directives from textual input. Extracted information is serialized into a platform-agnostic JSON intermediate representation, which drives automated 3D scene construction in Blender via the bpy Python API and in Unity via C# scripting. Experimental evaluation on twenty diverse cinematic scene descriptions demonstrates an average entity extraction accuracy of 87.5%, spatial relationship accuracy of 82.3%, lighting keyword detection of 94.1%, and camera directive extraction of 90.0%. The total pipeline latency from text input to rendered scene is under 6 seconds, validating the system's suitability for iterative use in real-world pre-production workflows. The system significantly reduces scene setup time and lowers the technical barrier for previsualization, offering a practical tool for the film, animation, and game production industries.