  An essential goal of computational media intelligence is to support
understanding how media stories -- be it news, commercial or entertainment
media -- represent and reflect society and these portrayals are perceived.
People are a central element of media stories. This paper focuses on
understanding the representation and depiction of background characters in
media depictions, primarily movies and TV shows. We define the background
characters as those who do not participate vocally in any scene throughout the
movie and address the problem of localizing background characters in videos. We
use an active speaker localization system to extract high-confidence
face-speech associations and generate audio-visual profiles for talking
characters in a movie by automatically clustering them. Using a face
verification system, we then prune all the face-tracks which match any of the
generated character profiles and obtain the background character face-tracks.
We curate a background character dataset which provides annotations for
background character for a set of TV shows, and use it to evaluate the
performance of the background character detection framework.
