An Individualized Face Pairing Model for Age-Invariant Face Recognition

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Joseph Damilola Akinyemi 1,* Olufade F. W. Onifade 1

1. Department of Computer Science, University of Ibadan, Ibadan, Nigeria

* Corresponding author.


Received: 11 Oct. 2022 / Revised: 25 Nov. 2022 / Accepted: 23 Dec. 2022 / Published: 8 Feb. 2023

Index Terms

Age-invariance, Facial Image Processing, Face Pairing, Face Recognition, Local Binary Patterns


Among other factors affecting face recognition and verification, the aging of individuals is a particularly challenging one. Unlike other factors such as pose, expression, and illumination, aging is uncontrollable, personalized, and takes place throughout human life. Thus, while the effects of factors such as head pose, illumination, and facial expression on face recognition can be minimized by using images from controlled environments, the effect of aging cannot be so controlled. This work exploits the personalized nature of aging to reduce the effect of aging on face recognition so that an individual can be correctly recognized across his/her different age-separated face images. To achieve this, an individualized face pairing method was developed in this work to pair faces against entire sets of faces grouped by individuals then, similarity score vectors are obtained for both matching and non-matching image-individual pairs, and the vectors are then used for age-invariant face recognition. This model has the advantage of being able to capture all possible face matchings (intra-class and inter-class) within a face dataset without having to compute all possible image-to-image pairs. This reduces the computational demand of the model without compromising the impact of the ageing factor on the identity of the human face. The developed model was evaluated on the publicly available FG-NET dataset, two subsets of the CACD dataset, and a locally obtained FAGE dataset using leave-one-person (LOPO) cross-validation. The model achieved recognition accuracies of 97.01%, 99.89%, 99.92%, and 99.53% respectively. The developed model can be used to improve face recognition models by making them robust to age-variations in individuals in the dataset.

Cite This Paper

Joseph Damilola Akinyemi, Olufade Falade Williams Onifade, "An Individualized Face Pairing Model for Age-Invariant Face Recognition", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.9, No.1, pp. 1-12, 2023. DOI: 10.5815/ijmsc.2023.01.01


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