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Robust face recognition by an albedo based 3D morphable model

Hu, G, Chan, CH, Yan, F, Christmas, W and Kittler, J (2014) Robust face recognition by an albedo based 3D morphable model

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Abstract

Large pose and illumination variations are very challenging for face recognition. The 3D Morphable Model (3DMM) approach is one of the effective methods for pose and illumination invariant face recognition. However, it is very difficult for the 3DMM to recover the illumination of the 2D input image because the ratio of the albedo and illumination contributions in a pixel intensity is ambiguous. Unlike the traditional idea of separating the albedo and illumination contributions using a 3DMM, we propose a novel Albedo Based 3D Morphable Model (AB3DMM), which removes the illumination component from the images using illumination normalisation in a preprocessing step. A comparative study of different illumination normalisation methods for this step is conducted on PIE and Multi-PIE databases. The results show that overall performance of our method outperforms state-of-the-art methods.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Hu, GUNSPECIFIEDUNSPECIFIED
Chan, CHUNSPECIFIEDUNSPECIFIED
Yan, FUNSPECIFIEDUNSPECIFIED
Christmas, WUNSPECIFIEDUNSPECIFIED
Kittler, JUNSPECIFIEDUNSPECIFIED
Date : 23 December 2014
Identification Number : 10.1109/BTAS.2014.6996223
Additional Information : © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 06 May 2015 09:03
Last Modified : 27 May 2015 13:33
URI: http://epubs.surrey.ac.uk/id/eprint/807514

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