This paper presents a novel approach for online subspace learning based on an incremental version of the nonparametric discriminant analysis (NDA). For many real-world applications...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level ...
In this paper, we propose an automatic method for the objective evaluation of segmentation results. The method is based on computing the deviation of the segmentation results from...
Andrea Cavallaro, Elisa Drelie Gelasca, Touradj Eb...
In the traditional data exchange setting, source instances are restricted to be complete in the sense that every fact is either true or false in these instances. Although natural ...