We explore the potential of Tensor-Train (TT) decompositions in the context of multi-feature face or object recognition strategies. We devise a new recognition algorithm that can handle three or more way tensors in the TT format, and propose a truncation strategy to limit memory usage. Numerical comparisons with other related methods—including the well established recognition algorithm based on high-order SVD—illustrate the features of the various strategies on benchmark datasets.
Tensor-Train decomposition for image recognition / Brandoni D.; Simoncini V.. - In: CALCOLO. - ISSN 0008-0624. - STAMPA. - 57:1(2020), pp. 9.1-9.24. [10.1007/s10092-020-0358-8]
Tensor-Train decomposition for image recognition
Brandoni D.;Simoncini V.
2020
Abstract
We explore the potential of Tensor-Train (TT) decompositions in the context of multi-feature face or object recognition strategies. We devise a new recognition algorithm that can handle three or more way tensors in the TT format, and propose a truncation strategy to limit memory usage. Numerical comparisons with other related methods—including the well established recognition algorithm based on high-order SVD—illustrate the features of the various strategies on benchmark datasets.| File | Dimensione | Formato | |
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TT_v3_revised_v2_bw.pdf
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