Feature extraction in 2D or 3D via histograms of normal Gabor-wavelets

Version 1.0.0.0 (237 KB) von Mehryar Emambakhsh
These functions compute normals of Gabor-wavelets and use spherical patches to extract features.
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Aktualisiert 24 Sep 2017

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This package implements the feature extraction algorithm using spherical patches from the Gabor-wavelet normal maps explained in:
M. Emambakhsh and A. Evans, “Nasal patches and curves for an expression-robust 3D face recognition,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 39, no. 5, pp. 995-1007, 2017.
Simply run the Demo_spherical_patched.m file to see a step by step output. Despite it is introduced for 3D face recognition, its applications can also be extended to other classes of 2D, 2.5D or 3D images, given a set of landmarks are available over the region.

Zitieren als

Mehryar Emambakhsh (2024). Feature extraction in 2D or 3D via histograms of normal Gabor-wavelets (https://www.mathworks.com/matlabcentral/fileexchange/63549-feature-extraction-in-2d-or-3d-via-histograms-of-normal-gabor-wavelets), MATLAB Central File Exchange. Abgerufen .

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Erstellt mit R2016b
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Spherical patches feature extraction/

Version Veröffentlicht Versionshinweise
1.0.0.0

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