We are entering an era of more intelligent cognitive vision systems. Such systems can
analyse activity in dynamic scenes to compute conceptual descriptions from motion …

In this paper we present results related to achieving finegrained activity recognition for
context-aware computing applications. We examine the advantages and challenges of …

Style translation is the process of transforming an input motion into a new style while
preserving its original content. This problem is motivated by the needs of interactive …

We present a novel approach for detecting social interactions in a crowded scene by
employing solely visual cues. The detection of social interactions in unconstrained scenarios …

This paper investigates the recognition of group actions in meetings. A framework is
employed in which group actions result from the interactions of the individual participants …

The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or
watching a video) a person is performing is of interest in many application domains. A …

Clustering of sequential or temporal data is more challenging than traditional clustering as
dynamic observations should be processed rather than static measures. This paper …

The future of artistic and expressive communication in the varied forms of film, theater,
dance, and narrative tends toward a blend of real and imaginary worlds in which moving …

I propose a common framework that combines three different paradigms in machine
learning: generative, discriminative and imitative learning. A generative probabilistic …

Hidden Markov models (HMM) are a widely used tool for sequence modelling. In the
sequence classification case, the standard approach consists of training one HMM for each …