Some effective techniques for recognizing a person across aging

Abstract

To identify a person across aging is a very challenging and interesting task. It has gained a lot of attention from the researchers as it has a wide range of real-life applications like finding missing children, renewal of passport, renewal of a driving license, finding criminals, etc. Many researchers have also proposed their own methodologies; still there is a gap to fill in. Hence, the authors have proposed some techniques for the betterment of the system performance. The first one is with GLBP as a novel feature, second with Convolutional Neural Network (CNN) and the last one is a modification of the previous method with biased face patches as inputs. CNN is found to be the perfect solution for face recognition problem over aging as there is no need for any complicated preprocessing and feature extraction steps. FGNET and MORPH II datasets are used for testing the performance of the system. All these techniques outperform available state-of-the-art methods in the Rank-1 recognition rate.