Face Identification using visible eye region via vanilla CNN and Siamese Networks
Vivek Dalai, K. V. Kadambari · 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022
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.