Structural perception of data plays a fundamental role in pattern analysis and machine learning. In this paper, we develop a new structural perception of data based on local conte...
We introduce the use of over-complete spherical wavelets for shape analysis of 2D closed surfaces. Bi-orthogonal spherical wavelets have been shown to be powerful tools in the seg...
Peng Yu, B. T. Thomas Yeo, P. Ellen Grant, Bruce F...
This paper shows that structure from motion is NP-hard for most sensible cost functions when missing data is allowed. The result provides a fundamental limitation of what is possi...
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
We present a novel level-set method for evolving open surfaces embedded in three-dimensional volumes. We adapt the method for statistical detection and segmentation of cytoarchite...
Biswajit Bose, John W. Fisher III, Bruce Fischl, O...
We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...
Numerical multilinear (tensor) algebra is a principled mathematical approach to disentangling and explicitly and parsimoniously representing the essential factors or modes of imag...
This paper presents a novel motion segmentation algorithm on the basis of mixture of Dirichlet process (MDP) models, a kind of nonparametric Bayesian framework. In contrast to pre...