This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Pervasive and ad hoc computing applications are frequently deployed in dynamic networks. Due to mobility of the computing nodes, their unreliability, or a limited communication ra...
In this paper, we propose a novel dynamic discrete framework to address image morphing with application to optical flow estimation. We reformulate the problem using a number of di...
Ben Glocker, Nikos Paragios, Nikos Komodakis, Geor...
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
Intrusion detection systems have become a key component in ensuring the safety of systems and networks. As networks grow in size and speed continues to increase, it is crucial tha...