Publication Date

Spring 2016

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Chris Pollett

Second Advisor

Jon Pearce

Third Advisor

Teng Moh

Keywords

Movie Script Parsing ans Shot Creation Naive Bayes

Abstract

The making of a motion picture almost always starts with the script, the written version of a story envisioned within the mind of its creator. The script is then broken down into shots. Each individual shot is filmed and then they are edited together to create the motion picture. The goal of the Movie Script Shot Lister thesis project is to be able to read in a script for a movie or television show, and automatically generate a shot list. While a script is text, a shot list is the blue print for how to visualize that script, so the shot lister tool will need some sort of information about the visuals and how they correspond to text that is written in the script. The basis of the lister is an application of artificial intelligence, a supervised learning algorithm to generate the shot list. First, training sets are generated by manually marking up scripts with shots. These training sets are fed into the program in order to give it a basic understanding of how to choose shots. The thesis project is composed of a few basic parts:

  •  a parser for procedurally breaking down a script into its components, which the rest of the program can use and understand;

  •  a lining tool for creating the training sets as well being a viewer for the final output;

  • a vector populator tool for processing the training sets and storing the data;

  • the lister tool itself which outputs a lined script;

  • and a comparer tool for comparing different outputs.

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