We introduce a nonlocal discrete regularization framework on weighted graphs of the arbitrary topologies for image and manifold processing. The approach considers the problem as a...
We describe an algorithm for similar-image search which
is designed to be efficient for extremely large collections of
images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
This paper improves recent methods for large scale image search. State-of-the-art methods build on the bag-of-features image representation. We, first, analyze bag-of-features in t...
In this paper we introduce a family of filter kernels the Gray-Code Kernels (GCK) and demonstrate their use in image analysis. Filtering an image with a sequence of Gray-Code Kern...