In this paper we propose a novel solution to the multi-view matching problem that, given a set of noisy pairwise correspondences, jointly updates them so as to maximize their consistency. Our method is based on a spectral decomposition, resulting in a closed-form efficient algorithm, in contrast to other iterative techniques that can be found in the literature. Experiments on both synthetic and real datasets show that our method achieves comparable or superior accuracy to state-of-the-art algorithms in significantly less time. We also demonstrate that our solution can efficiently handle datasets of hundreds of images, which is unprecedented in the literature
We present an efficient spectral method for finding consistent correspondences between two sets of f...
In this paper we introduce a robust matching technique that allows very accurate selection of corres...
Joint matching over a collection of objects aims at aggregating information from a large collection ...
In this paper we propose a novel solution to the multi-view matching problem that, given a set of no...
Spectral decomposition subject to pairwise geometric constraints is one of the most successful image...
In this paper we introduce a robust matching technique that allows very accurate selection of corres...
There are many approaches being proposed to find the correspondence points between two images. They ...
Establishing the correct correspondence between features in an image set remains a challenging probl...
We present an efficient spectral method for finding consistent correspondences between two sets of f...
Multi-view point registration is a relatively less studied problem compared with two-view point regi...
The problem of determining feature correspondences across multiple views is considered. The term &qu...
In this paper we introduce a robust matching tech-nique that allows to operate a very accurate selec...
We propose a correspondence matching algorithm for multi-view video sequences, which provides reliab...
Considering n pairwise feature correspondences we want sets of cor-responding matching features acro...
We present a robust feature matching approach that considers features from more than two images duri...
We present an efficient spectral method for finding consistent correspondences between two sets of f...
In this paper we introduce a robust matching technique that allows very accurate selection of corres...
Joint matching over a collection of objects aims at aggregating information from a large collection ...
In this paper we propose a novel solution to the multi-view matching problem that, given a set of no...
Spectral decomposition subject to pairwise geometric constraints is one of the most successful image...
In this paper we introduce a robust matching technique that allows very accurate selection of corres...
There are many approaches being proposed to find the correspondence points between two images. They ...
Establishing the correct correspondence between features in an image set remains a challenging probl...
We present an efficient spectral method for finding consistent correspondences between two sets of f...
Multi-view point registration is a relatively less studied problem compared with two-view point regi...
The problem of determining feature correspondences across multiple views is considered. The term &qu...
In this paper we introduce a robust matching tech-nique that allows to operate a very accurate selec...
We propose a correspondence matching algorithm for multi-view video sequences, which provides reliab...
Considering n pairwise feature correspondences we want sets of cor-responding matching features acro...
We present a robust feature matching approach that considers features from more than two images duri...
We present an efficient spectral method for finding consistent correspondences between two sets of f...
In this paper we introduce a robust matching technique that allows very accurate selection of corres...
Joint matching over a collection of objects aims at aggregating information from a large collection ...