The problem of matching not just two, but m different sets of objects to each other arises in a
variety of contexts, including finding the correspondence between feature points across …

In this paper we propose a global optimization-based approach to jointly matching a set of
images. The estimated correspondences simultaneously maximize pairwise feature affinities …

We consider the problem of finding consistent matches across multiple images. Current state-
of-the-art solutions use constraints on cycles of matches together with convex optimization …

We present a convex relaxation for the multi-graph matching problem. Our formulation
allows for partial pairwise matchings, guarantees cycle consistency, and our objective …

Joint matching over a collection of objects aims at aggregating information from a large
collection of similar instances (eg images, graphs, shapes) to improve maps between pairs …

The problem of matching two sets of features appears in various tasks of computer vision
and can be often formalized as a problem of permutation estimation. We address this …

In this paper, we present a new approach for establishing correspondences between sparse
image features related by an unknown nonrigid mapping and corrupted by clutter and …

Elimination Algorithms are often used in template matching to provide a significant speed-up
by skipping portions of the computation while guaranteeing the same best-match location as …

This article presents a signal matching algorithm that can select an appropriate window size
adaptively so as to obtain both precise and stable estimation of correspondences. Matching …

A theoretical framework is presented in which windowed Fourier phase (WFP) is introduced
as the primary matching primitive. Zero-crossings and peaks correspond to special values of …