Robust Face Verification using Skin Color and Neural Networks

The performance of face verification systems has steadily improved over the last few years. State-of-the-art methods often use the gray-scale face image as input. In this paper, we use an additional feature to the face image: the skin color. The feature set is tested on a benchmark database, namely XM2VTS, using a simple discriminant artificial neural network. Results show that the proposed model achieves robust state-of-the-art results.


Year:
2002
Publisher:
IDIAP
Keywords:
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 Record created 2006-03-10, last modified 2018-03-17

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