We proposes a practical technique for the classification of facial images across multiple criteria, such as: gender, age, ethnicity, expression, and others. The technique uses a novel form of Gabor-based features followed by the application of the PCA and LDA algorithms. The computation of class scores in the context of nearest centroid classification is also novel, and relies, in part, on properties of the proposed features. We demonstrate that the proposed form of Gabor features is particularly suitable for achieving simultaneous classification. The reported results are obtained using a set of standard databases and include comparisons against known state-of-the-art algorithms. The utility of the proposed scheme is demonstrated by practical applications requiring multiple classification results to be obtained in real time while using typical consumer devices (cellphones, tablets, PCs) as computing platforms.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.