RASL robust alignment by sparse and low-rank decomposition for linearly correlated images

RASL : robust alignment by sparse and low-rank decomposition for linearly correlated images

This paper studies the problem of simultaneously aligning a batch of linearly correlated images despite gross corruption (such as occlusion). Our method seeks an optimal set of image domain transformations such that the matrix of transformed images can be decomposed as the sum of a sparse matrix of...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 34(2012), 11 vom: 05. Nov., Seite 2233-46
1. Verfasser: Peng, Yigang (VerfasserIn)
Weitere Verfasser: Ganesh, Arvind, Wright, John, Xu, Wenli, Ma, Yi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2012
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S.