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Conformal Mapping of a 3D Face Representation onto a 2D Image for CNN Based Face Recognition

Kittler, Josef, Koppen, Paul, Kopp, Philipp, Huber, Patrik and Rätsch, Matthias (2018) Conformal Mapping of a 3D Face Representation onto a 2D Image for CNN Based Face Recognition In: 11th International Conference on Biometrics (ICB) 2018, 20 - 23 February 2018, Gold Coast, QLD, Australia.

Full text not available from this repository.
Official URL: http://icb2018.org/

Abstract

Fitting 3D Morphable Face Models (3DMM) to a 2D face image allows the separation of face shape from skin texture, as well as correction for face expression. However, the recovered 3D face representation is not readily amenable to processing by convolutional neural networks (CNN). We propose a conformal mapping from a 3D mesh to a 2D image, which makes these machine learning tools accessible by 3D face data. Experiments with a CNN based face recognition system designed using the proposed representation have been carried out to validate the advocated approach. The results obtained on standard benchmarking data sets show its promise.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Kittler, JosefJ.Kittler@surrey.ac.uk
Koppen, Paulp.koppen@surrey.ac.uk
Kopp, Philipp
Huber, Patrikp.huber@surrey.ac.uk
Rätsch, Matthias
Date : 16 July 2018
DOI : 10.1109/ICB2018.2018.00029
Depositing User : Melanie Hughes
Date Deposited : 17 Oct 2018 09:39
Last Modified : 17 Oct 2018 09:39
URI: http://epubs.surrey.ac.uk/id/eprint/849705

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