To investigate the impact of audiovisual features extracted from the movie trailer content to be used as input along with the metadata to predict the movie's opening weekend gross. The author argues that the use of audiovisual features is expected to improve the prediction performance.

1- The audiovisual features from the trailers had to be extracted manually to be used as inputs. The choice of audiovisual features is such that they are related to certain metadata features
2- The author investigate the usefulness of the selected audiovisual features in explaining certain metadata features. Linear SVM was used to predict the category of genre and MPAA rating using audiovisuals. Then for continuous metadata features (budget, movie runtime, etc), linear regression was used. It was found that some metadata can be replaced with audiovisuals. For example, movie genre, it can be easily predicted from the movie trailer.
3- After investigating the usefulness of audiovisuals, the author proceeded to find the correlation between the extracted audiovisuals and the opening weekend gross of the movie. Results from this are in "Results of Study"

This model can be modified to learn and extract the audiovisuals instead of extracting them manually