Leveraging implicit demographic information for face recognition using a multi-expert system
This paper describes a novel biometric architecture to implement unsupervised face recognition across varying demographics. The present proposal deals with ethnicity, gender and age, but the same strategy can be crafted for any mix of soft/hard biometrics, sensors, and/or methods. Our aim is not to explicitly distinguish demographic features of a subject (e.g., male vs. female). We rather aim at implicitly exploiting such information to improve the accuracy of subject identification. The role demographics plays in authentication has been reported by many recent studies.