Indefinite kernels arise in practice, e.g. from problem-specific kernel construction. Therefore, it is necessary to understand the behavior and suitability of classifiers in the c...
General dissimilarity-based learning approaches have been proposed for dissimilarity data sets [11, 10]. They arise in problems in which direct comparisons of objects are made, e....
In this paper we propose a novel approach to the perceptual interpretation of building facades that combines shape grammars, supervised classification and random walks. Procedural...
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled f...
This paper presents an efficient Real-Time method for detecting moving objects in unconstrained environments, using a background subtraction technique. A new background model that...
Ariel Amato, Mikhail Mozerov, Ivan Huerta Casado, ...