We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
This paper describes an approach for generating Binary Partition Tree [7] representations and video object segmentations using a novel region merging strategy based on motion simi...
We develop a framework for the image segmentation problem based on a new graph-theoretic formulation of clustering. The approach is motivated by the analogies between the intuitiv...
A global parametric shape model (boundary) of the object is optimized according to evidence accumulated from local features and the prior probability of the model parameters learn...
We address the question of how to choose between different likelihood functions for motion estimation. To this end, we formulate motion estimation as a problem of Bayesian inferen...