In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
This paper presents an efficient method to integrate various spatial-temporal constraints to regularize the contour tracking. The global shape of the contour is represented in a p...
We present a novel approach for visual tracking of structured behaviour as observed in human–computer interaction. An automatically acquired variable-length Markov model is used...
Nikolay Stefanov, Aphrodite Galata, Roger J. Hubbo...
We propose a novel tracking framework called visual tracker sampler that tracks a target robustly by searching for the appropriate trackers in each frame. Since the real-world trac...