DocumentCode
3672287
Title
A solution for multi-alignment by transformation synchronisation
Author
Florian Bernard;Johan Thunberg;Peter Gemmar;Frank Hertel;Andreas Husch;Jorge Goncalves
Author_Institution
Centre Hospitalier de Luxembourg, Luxembourg
fYear
2015
fDate
6/1/2015 12:00:00 AM
Firstpage
2161
Lastpage
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.
Keywords
"Noise measurement","Null space","Shape","Noise","Synchronization","Iterative methods","Computational modeling"
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2015.7298828
Filename
7298828
Link To Document