Tracking and identifying players in sports videos filmed with a single pan-tilt-zoom camera
has many applications, but it is also a challenging problem. This paper introduces a system …

The goal of face identification is to decide whether two faces depict the same person or not.
This paper addresses the identification problem for face-tracks that are automatically …

Understanding videos such as TV series and movies requires analyzing who the characters
are and what they are doing. We address the challenging problem of clustering face tracks …

We describe a probabilistic method for identifying characters in TV series or movies. We aim
at labeling every character appearance, and not only those where a face can be detected …

In this paper, we focus on face clustering in videos. To promote the performance of video
clustering by multiple intrinsic cues, ie, pairwise constraints and multiple views, we propose …

The objective of this work is person-clustering in videos--grouping characters according to
their identity. Previous methods focus on the narrower task of face-clustering, and for the …

We present a novel way to automatically summarize and represent the storyline of a TV
episode by visualizing character interactions as a chart. We also propose a scene detection …

The task of searching certain people in videos has seen increasing potential in real-world
applications, such as video organization and editing. Most existing approaches are devised …

The goal of this paper is the automatic identification of characters in TV and feature film
material. In contrast to standard approaches to this task, which rely on the weak supervision …

We propose a method to facilitate search through the storyline of TV series episodes. To this
end, we use human written, crowdsourced descriptions—plot synopses—of the story …