multiviewregistration is an important stage in three-dimensional modelling pipeline. Motion averaging is an efficient approach for multiviewregistration which utilises the redundancy in overlap among the scans. The ...
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multiviewregistration is an important stage in three-dimensional modelling pipeline. Motion averaging is an efficient approach for multiviewregistration which utilises the redundancy in overlap among the scans. The averaging of the underlying relative motions is performed in the corresponding Lie-algebra elements of the SE(3) transformation matrices. However, this method is non-robust and affected by the presence of outliers in the set of relative motions. The authors present a graph-based approach to filter out the outliers before performing averaging of motions. The relative motions are assigned weights based on their agreement with global motions and other relative motions. The results indicate that the authors' approach can efficiently filter out the outliers and can thus introduce robustness to multiviewregistration using motion averaging.
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