The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspond...
The Cluster-Weighted Modeling (CWM) is emerging as a versatile tool for modeling dynamical systems. It is a mixture density estimator around local models. To be specific, the inpu...
Compositional Scheduling Analysis couples local scheduling analysis via event streams. While local analysis has successfully been extended to include hierarchical scheduling strat...
Imitation-based learning is a general mechanism for rapid acquisition of new behaviors in autonomous agents and robots. In this paper, we propose a new approach to learning by imit...