In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
Instead of the conventional background and foreground definition, we propose a novel method that decomposes a scene into time-varying background and foreground intrinsic images. T...
Abstract. Virtually all variational methods for motion estimation regularize the gradient of the flow field, which introduces a bias towards piecewise constant motions in weakly te...
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...
Frames of videos with static background and dynamic foreground can be viewed as samples of signals that vary slowly in time with sparse corruption caused by foreground objects. We...
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...