Face Identification using visible eye region via vanilla CNN and Siamese Networks

Human faces being highly dynamic, are extensively studied in the field of pattern recognition, computer vision and artificial intelligence. Moreover, identification of faces using a part of it still remains an understudied domain. Detection of faces using just uncovered eye images can be a boon for surveillance and security especially in times of Covid-19 when most people are advised to cover their faces in a pub-lic space. In this paper we present a system, which identifies the person's face using the visible eye region namely the eyes and the forehead portions of the per-son. The model is trained over basic convolution net-work and the classification is done using Siamese net-works. The classification accuracy is measured using the dis-similarity score which calculates the euclidean distance between the converted feature vectors of the eye regions. The regions which are similar have neg-ligible dissimilarity score.