A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Abstract. Understanding texture regularity in real images is a challenging computer vision task. We propose a higher-order feature matching algorithm to discover the lattices of ne...
James Hays, Marius Leordeanu, Alexei A. Efros, Yan...
In this paper we establish a topological similarity between two apparently different shape constructors from a set of points. Shape constructors are geometric structures that tran...
In this paper we present algorithms for a number of problems in geometric pattern matching where the input consist of a collections of segments in the plane. Our work consists of ...
Alon Efrat, Piotr Indyk, Suresh Venkatasubramanian