The past number of years has seen a large increase in the number of movies, and therefore movie databases, created. As movies are typically quite long, locating relevant clips in these databases is quite difficult unless a well defined index is in place. As movies are creatively made, creating automatic indexing algorithms is a challenging task. However, there are a number of underlying film grammar principles that are universally followed. By detecting and examining the use of these principles, it is possible to extract information about the occurrences of specific events in a movie. This work attempts to completely index a movie by detecting all of the relevant events. The event detection process involves examining the underlying structure of a movie and utilising audiovisual analysis techniques, supported by machine learning algorithms, to extract information based on this structure. This results in a summarised and indexed movie.