Many social networks can be characterized by a sequence of dyadic interactions between individuals. Techniques for analyzing such events are of increasing interest. In this paper,...
Abstract— For many tasks in populated environments, robots need to keep track of present and future motion states of people. Most approaches to people tracking make weak assumpti...
Matthias Luber, Johannes Andreas Stork, Gian Diego...
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Abstract--This paper proposes a no-reference quality assessment metric for digital video subject to H.264/AVC encoding. The proposed metric comprises two main steps: coding error e...