For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a un...
Given an image sequence of a scene consisting of multiple rigidly moving objects, multi-body structure-and-motion (MSaM) is the task to segment the image feature tracks into the d...
Most recent class-level object recognition systems work with visual words, i.e., vector quantized local descriptors. In this paper we examine the feasibility of a dataindependent ...