This paper proposes a new background subtraction method for detecting moving objects from a time-varied background. While background subtraction has traditionally worked well for ...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
We propose a novel approach to modeling prosodic features. Inspired by Joint Factor Analysis model (JFA), our model is based on the same idea of introducing subspace of model para...
Marcel Kockmann, Lukas Burget, Ondrej Glembek, Luc...
This research investigates distributed clustering scheme and proposes a cluster-based routing protocol for DelayTolerant Mobile Networks (DTMNs). The basic idea is to distributivel...
In this paper we perform 3D face tracking on corrupted video sequences. We use a deformable model, combined with a predictive filter, to recover both the rigid transformations and...
Siome Goldenstein, Christian Vogler, Dimitris N. M...