Improving Face Verification using Skin Color Information

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 significantly the performance.


Year:
2001
Publisher:
IDIAP
Keywords:
Note:
Published in the Proceedings of the International {C}onference on {P}attern {R}ecognition, Quebec City, Canada, 2002
Laboratories:




 Record created 2006-03-10, last modified 2018-03-17

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