We present a fast pattern matching algorithm with a large set of templates. The algorithm is
based on the typical template matching speeded up by the dual decomposition; the Fourier …

Stereo matching is an ill-posed problem for at least two principal reasons:(1) because of the
random nature of match similarity measure and (2) because of structural ambiguity due to …

Graph matching-aligning a pair of graphs to minimize their edge disagreements-has
received wide-spread attention from both theoretical and applied communities over the past …

We propose a new error measure for matching pixels that is based on co-occurrence
statistics. The measure relies on a co-occurrence matrix that counts the number of times …

This paper challenges the issue of automatic matching between two image sets with similar
intrinsic structures and different appearances, especially when there is no prior …

Affine transformations of the plane have been used by modelbased recognition systems to
approximate the effects of perspective projection. Because the underlying mathematics are …

This paper presents a novel method for addressing the problem of finding more good feature
pairs between images, which is one of the most fundamental tasks in computer vision and …

A stochastic optimization approach to stereo matching is presented. Unlike conventional
correlation matching and feature matching, the method provides a dense array of disparities …

Feature matching is a key problem in computer vision and pattern recognition. One way to
encode the essential interdependence between potential feature matches is to cast the …

A new robust matching method is proposed. The progressive sample consensus (PROSAC)
algorithm exploits the linear ordering defined on the set of correspondences by a similarity …