A framework for joint estimation of age, gender and ethnicity on a large database

• Published in: Image and vision computing Vol. 32; no. 10; pp. 761 - 770
• Main Authors: Guo, Guodong, Mu, Guowang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2014
• Subjects: A general framework; Canonical correlation analysis (CCA); Joint estimation of age, gender and ethnicity; Kernel CCA (KCCA); Kernel PLS (KPLS); Least squares CCA; Partial least squares (PLS); Regularized CCA; Regularized KCCA; Kernel PLS (KPLS); Least squares CCA; Partial least squares (PLS); Joint estimation of age, gender and ethnicity; Regularized CCA; A general framework; Regularized KCCA; Canonical correlation analysis (CCA); Kernel CCA (KCCA)

Human age, gender and ethnicity are valuable demographic characteristics. They are also important soft biometric traits useful for human identification or verification. We present a framework that can estimate the three traits jointly. The joint estimation framework could deal with the mutual influe...