Title :
Affine Invariance Revisited
Author :
Begelfor, Evgeni ; Werman, Michael
Author_Institution :
Hebrew University of Jerusalem
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.
Keywords :
Clustering algorithms; Computer science; Computer vision; Covariance matrix; Distributed computing; Geometry; Probability distribution; Robustness; Shape; Statistics;
Conference_Titel :
Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on
Print_ISBN :
0-7695-2597-0
DOI :
10.1109/CVPR.2006.50
