A State-of-the-art Neural Network for Robust Face Verification
| Type of publication: | Idiap-RR |
| Citation: | Marcel02-36IRR |
| Number: | Idiap-RR-36-2002 |
| Year: | 2002 |
| Institution: | IDIAP |
| Note: | Published in the Proceedings of the COST275 Workshop on The Advent of Biometrics on the Internet, Rome, Italy, 7-8 November, 2002 |
| Abstract: | The performance of face verification systems has steadily improved over the last few years, mainly focusing on models rather than on feature processing. State-of-the-art methods often use the gray-scale face image as input. In this paper, we propose to use an additional feature to the face image: the skin color. The new feature set is tested on a benchmark database, namely XM2VTS, using a simple discriminant artificial neural network. Results show that the skin color information improves the performance and that the proposed model achieves robust state-of-the-art results. |
| Userfields: | ipdinar={2002}, ipdmembership={learning, vision}, language={English}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Crossref by |
marcel:2002:cost |
| Added by: | [UNK] |
| Total mark: | 0 |
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