853 research outputs found
A Solution for Multi-Alignment by Transformation Synchronisation
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.Comment: Accepted for CVPR 2015 (please cite CVPR version
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