Abstract

The expanding interest in automatic age and gender prediction from facial images has sparked significant research attention due to its wide applicability in various facial analyses. This paper explores the use of support vector machine (SVM) algorithms, along with associated methodologies, to enable gender classification and age detection from single glimpses captured by cameras, images, or videos. It aims to clarify the integration of these techniques and their significance in enhancing everyday life. The primary goal is to employ SVM models to develop a gender and age detection system capable of providing approximate predictions for individuals depicted in images. In this paper real-world images are taken and applied to the SVM algorithm. Additionally, this paper explores the potential applications of such technology, spanning intelligence agencies, surveillance systems like CCTV, policing, and matchmaking platforms.