Blur-Invariant Similarity Measurement of Images

This article is a comment on the recent TPAMI paper (Gopalan et al. , 2012) that introduced a blur-invariant distance measure between two images. We point out two mistakes of the theory presented in (Gopalan et al. , 2012) and propose a correction. We also compare the original and corrected methods...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2021-08, Vol.43 (8), p.2882-2884
Hauptverfasser:	Lebl, Matej, Sroubek, Filip, Flusser, Jan
Format:	Artikel
Sprache:	eng
Schlagworte:	Blurred image classification constrained minimization Convolution Distance measurement Face recognition Image recognition invariant distance Invariants Kernel Manifolds Measurement Minimization subspace projections
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creator	Lebl, Matej Sroubek, Filip Flusser, Jan
description	This article is a comment on the recent TPAMI paper (Gopalan et al. , 2012) that introduced a blur-invariant distance measure between two images. We point out two mistakes of the theory presented in (Gopalan et al. , 2012) and propose a correction. We also compare the original and corrected methods experimentally.
doi_str_mv	10.1109/TPAMI.2020.3036630
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subjects	Blurred image classification constrained minimization Convolution Distance measurement Face recognition Image recognition invariant distance Invariants Kernel Manifolds Measurement Minimization subspace projections
title	Blur-Invariant Similarity Measurement of Images
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