Movie genre classification by exploiting MEG brain signals

Abstract

Genre classification is an essential part of multimedia content recommender systems. In this study, we provide experimental evidence for the possibility of performing genre classification based on brain recorded signals. The brain decoding paradigm is employed to classify magnetoencephalography (MEG) data presented in [1] to four genre classes: Comedy, Romantic, Drama, and Horror. Our results show that: 1) there is a significant correlation between audio-visual features of movies and corresponding brain signals specially in the visual and temporal lobes; 2) the genre of movie clips can be classified with an accuracy significantly over the chance level using the MEG signal. On top of that we show that the combination of multimedia features and MEG-based features achieves the best accuracy. Our study provides a primary step towards user-centric media content retrieval using brain signals.