In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
This paper introduces an edge-based object recognition method that is robust with respect to clutter, occlusion and object deformations. The method combines the use of local featu...
A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
Abstract. Robust object recognition is one of the most challenging topics in computer vision. In the last years promising results have been obtained using local regions and descrip...