Given a set of n points in d-dimensional Euclidean space, S ⊂ Ed , and a query point q ∈ Ed , we wish to determine the nearest neighbor of q, that is, the point of S whose Euc...
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
We present a new method for generating large numbers of accurate point correspondences between two wide baseline images. This is important for structure-from-motion algorithms, wh...
Local feature approaches to vision geometry and object recognition are based on selecting and matching sparse sets of visually salient image points, known as `keypoints' or `p...
This paper addresses the problem of finding a small and coherent subset of points in a given data. This problem, sometimes referred to as one-class or set covering, requires to fi...