Face verification using competitive negative samples
Ding Xiaoqing · Journal of Tsinghua University(Science and Technology) · 2004
A novel verification algorithm was proposed using competitive negative samples to enhance discrimination in face verification. In the algorithm, the test face was matched not only with the claimed client face, but also with competitive negative samples, with all the matching scores combined for a final decision. Three schemes were designed. They were the closest-negative- sample scheme, the all-negative-sample scheme, and the closest- few-negative-sample scheme. The schemes were compared with the traditional similarity-based verification approach on several databases, features and classifiers. The tests demonstrat that the three schemes reduced the verification error rate by 25.13%, 30.24% and 30.97% on average.