Analysis of Age Invariant Face Recognition Efficiency Using Face Feature Vectors

One of the main problems for face recognition when comparing photos of various ages is the impact of age progression on facial features. The face undergoes many changes as a person grows older, including geometrical changes and changes in facial hair, etc. Even though biometric markers such as computed face feature vectors should preferably be invariant to such factors, face recognition generally becomes less reliable as the age span grows larger. Therefore, this study was conducted with the aim of exploring the efficiency of such feature vectors in recognising individuals despite variations in age, and how to measure face recognition performance and behaviour in the data. It is shown that they are indeed discriminative enough to achieve age-invariant face recognition without synthesising age images through generative processes or training on specialised age related features.