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ICCV
2003
IEEE

Spectral Partitioning for Structure from Motion

15 years 25 days ago
Spectral Partitioning for Structure from Motion
We propose a spectral partitioning approach for large-scale optimization problems, specifically structure from motion. In structure from motion, partitioning methods reduce the problem into smaller and better conditioned subproblems which can be efficiently optimized. Our partitioning method uses only the Hessian of the reprojection error and its eigenvectors. We show that partitioned systems that preserve the eigenvectors corresponding to small eigenvalues result in lower residual error when optimized. We create partitions by clustering the entries of the eigenvectors of the Hessian corresponding to small eigenvalues. This is a more general technique than relying on domain knowledge and heuristics such as bottom-up structure from motion approaches. Simultaneously, it takes advantage of more information than generic matrix partitioning algorithms.
Drew Steedly, Irfan A. Essa, Frank Dellaert
Added 15 Oct 2009
Updated 31 Oct 2009
Type Conference
Year 2003
Where ICCV
Authors Drew Steedly, Irfan A. Essa, Frank Dellaert
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