A Solution for Multi-Alignment by Transformation Synchronisation

Florian Bernard, Johan Thunberg, Peter Gemmar, Frank Hertel, Andreas Husch, Jorge Goncalves; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2161-2169

Abstract


The alignment of a set of objects by means of transformations plays an important role in computer vision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used. In practice the iterative methods perform well if the relative transformations between any pair of objects are free of noise. However, if only noisy relative transformations are available (e.g. due to missing data or wrong correspondences) the iterative methods may fail. Based on the observation that the underlying noise-free transformations can be retrieved from the null space of a matrix that can directly be obtained from pairwise alignments, this paper presents a novel method for the synchronisation of pairwise transformations such that they are transitively consistent. Simulations demonstrate that for noisy transformations, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.

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[bibtex]
@InProceedings{Bernard_2015_CVPR,
author = {Bernard, Florian and Thunberg, Johan and Gemmar, Peter and Hertel, Frank and Husch, Andreas and Goncalves, Jorge},
title = {A Solution for Multi-Alignment by Transformation Synchronisation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}