Conformal mapping of a 3D face representation onto a 2D image for CNN based face recognition

  • 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.

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Metadaten
Name:Rätsch, Matthias
DOI:https://doi.org/10.1109/ICB2018.2018.00029
ISBN:978-1-5386-4285-6
Erschienen in:2018 International Conference on Biometrics : ICB 2018 : Gold Coast, Queensland, Australia, 20-23 February 2018, proceedings
Publisher:IEEE
Place of publication:Piscataway, NJ
Document Type:Conference Proceeding
Language:English
Year of Publication:2018
Pagenumber:8
First Page:124
Last Page:131
Dewey Decimal Classification:004 Informatik
Open Access:Nein
Licence (German):License Logo  Lizenzbedingungen IEEE