This paper proposes an approach for recognizing human activities (more specifically, pedestrian trajectories) in video sequences, in a surveillance context. A system for automatic ...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
We present an artificially simulated dataset (TIED) constructed so that there are many minimal sets of variables with maximal predictivity (i.e., Markov boundaries) and likewise m...
In this paper we study various chain codes, which are representations of binary image contours, in terms of their ability to compress in the best way the contour information using...