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ICPR
2002
IEEE

A Fast Leading Eigenvector Approximation for Segmentation and Grouping

9 years 11 months ago
A Fast Leading Eigenvector Approximation for Segmentation and Grouping
We present a fast non-iterative method for approximating the leading eigenvector so as to render graph-spectral based grouping algorithms more efficient. The approximation is based on a linear perturbation analysis and applies to matrices that are non-sparse, non-negative and symmetric. For an ? ? ? matrix, the approximation can be implemented with complexity as low as ? ??.We provide a performance analysis and demonstrate the usefulness of our method on image segmentation problems.
Antonio Robles-Kelly, Sudeep Sarkar, Edwin R. Hanc
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2002
Where ICPR
Authors Antonio Robles-Kelly, Sudeep Sarkar, Edwin R. Hancock
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