Reference : A solution for Multi-Alignment by Transformation Synchronisation
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/10993/20807
A solution for Multi-Alignment by Transformation Synchronisation
English
Bernard, Florian mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)]
Thunberg, Johan mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Gemmar, Peter [> >]
Hertel, Frank mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Husch, Andreas mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)]
Goncalves, Jorge mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
2015
The proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
IEEE
Yes
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
8-10 June, 2015
Boston
USA
[en] 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 lie in 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 globally consistent. Simulations demonstrate that for a high amount of noise, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.
http://hdl.handle.net/10993/20807
arXiv:1410.8546
FnR ; FNR8864515 > Johan Thunberg > > Set Convergence in Nonlinear Multi-Agent Systems > 01/02/2015 > 31/01/2017 > 2014

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