Machine Learning in Storyboarding and Storytelling

This paper will interrogate and discuss the possibility of applying machine learning technology into storyboarding processes from an animation and film industry perspective. In current animation or film production studios, most of a storyboarder's creative process is a repeating step of manually editing and visualizing content from a script. It is a storyboarders’ responsibility to analyze camera cuts and scenes information, then organize the scenes, the director's notes, and camera movements in storyboard drawing software to create a working template. The storyboarder is always responsible for hundreds of such repeating steps in storyboarding processes. Those repeating actions are all inefficient and could be limiting. This paper will analyze and review many machine learning technology methods in the current animation and film industry. The literature review part will identify many machine learning methods’ positions in the animation production pipeline and their advantages and disadvantages in related professional fields. Finally, this research paper will address a theoretical concept of applying visual recognition, text mining and automation technology into storyboarding software to analyze the scripts for storyboarders.