Affine Invariance Revisited

Authors:
Evgeni Begelfor;Michael Werman
Affiliations:
Hebrew University of Jerusalem;Hebrew University of Jerusalem
Venue:
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Year:
2006

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Abstract

This paper proposes a Riemannian geometric framework to compute averages and distributions of point configurations so that different configurations up to affine transformations are considered to be the same. The algorithms are fast and proven to be robust both theoretically and empirically. The utility of this framework is shown in a number of affine invariant clustering algorithms on image point data.