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Lecture Notes in Computer Science
Performances of face recognition systems based on principal component analysis can degrade quickly when input images exhibit substantial variations, due for example to changes in illumination or pose, compared to the templates collected during the enrolment stage. On the other hand, a lot of new unlabelled face images, which could be potentially used to update the templates and re-train the system, are made available during the system operation. In this paper a semi-supervised version, based ondoi:10.1007/11815921_61 fatcat:6sqebq3yzre5ffxydbvraybhwi