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- W2126954187 abstract "This paper addresses the problem of establishing point correspondences between two object instances using spectral high-order graph matching. Therefore, 3D objects are intrinsically represented by weighted high-order adjacency tensors. These are, depending on the weighting scheme, invariant for structure-preserving, equi-areal, conformal or volume-preserving object deformations. Higher-order spectral decomposition transforms the NP-hard assignment problem into a linear assignment problem by canonical embedding. This allows to extract dense correspondence information with reasonable computational complexity, making the method faster than any other previously published method imposing higher-order constraints to shape matching. Robustness against missing data and resampling is measured and compared with a baseline spectral graph matching method." @default.
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- W2126954187 date "2011-06-01" @default.
- W2126954187 modified "2023-10-14" @default.
- W2126954187 title "Dense shape correspondences using spectral high-order graph matching" @default.
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- W2126954187 doi "https://doi.org/10.1109/cvprw.2011.5981675" @default.
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