We propose a method for measuring the quality of a grouping result, based on the following observation: a better grouping result provides more information about the true, unknown g...
Erik A. Engbers, Michael Lindenbaum, Arnold W. M. ...
This paper addresses the challenge of recognizing behavior of groups of individuals in unconstraint surveillance environments. As opposed to approaches that rely on agglomerative ...
Noise confounds present serious complications to accurate data analysis in functional magnetic resonance imaging (fMRI). Simply relying on contextual image information often resul...
Skeletonization algorithms typically decompose an object’s
silhouette into a set of symmetric parts, offering a
powerful representation for shape categorization. However,
havi...
Alex Levinshtein, Sven Dickinson, Cristian Sminchi...
Multibody grouping is a representative of applying subspace constraints in computer vision tasks. Under linear projection models, feature points of multibody reside in multiple su...