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.
| Author of HS Reutlingen | 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 |
| Page Number: | 8 |
| First Page: | 124 |
| Last Page: | 131 |
| DDC classes: | 004 Informatik |
| Open Access?: | Nein |
| Licence (German): |  Lizenzbedingungen IEEE |
