Color-mood analysis of films based on syntactic and psychological models

The emergence of peer-to-peer networking and the increase of home PC storage capacity are necessitating efficient scaleable methods for video clustering, recommending and browsing. Based on film theories and psychological models, color-mood is an important factor affecting user emotional preferences. We propose a compact set of features for color-mood analysis and subgenre discrimination. We introduce two color representations for scenes and full films in order to extract the essential moods from the films: a global measure for the color palette and a discriminative measure for the transitions of the moods in the movie. We captured the dominant color ratio and the pace of the movie. Despite the simplicity and efficiency of the features, the classification accuracy was surprisingly good, about 80%, possibly thanks to the prevalence of the color-mood association in feature films.