A method for estimating age and gender using multiple local patches is proposed in this thesis. We use the histogram of rotation-invariant local binary pattern as our features to train the SVM model. We further introduce the shifting and scaling of the local patches to enhance the accuracy of the estimation. Our proposed method not only provides accurate results but also can be incorporated with other methods to further improve their accuracy.
