A Method Based on Active Appearance Model and Gradient Orientation Pyramid of Face Verification as People Age

Abstract

Face verification in the presence of age progression is an important problem that has not been widely addressed. In this paper, we propose to use the active appearance model (AAM) and gradient orientation pyramid (GOP) feature representation for this problem. First, we use the AAM on the dataset and generate the AAM images; we then get the representation of gradient orientation on a hierarchical model, which is the appearance of GOP. When combined with a support vector machine (SVM), experimental results show that our approach has excellent performance on two public domain face aging datasets: FGNET and MORPH. Second, we compare the performance of the proposed methods with a number of related face verification methods; the results show that the new approach is more robust and performs better.