Comparative Analysis of Clustering Algorithm for Facial Recognition System

Abstract

A large part of the video surveillance systems involves dealing with face detection techniques on unlabeled faces. We define several classes of faces to detect them from a surveillance footage defined using different clustering algorithms. In this paper, authors have proposed a facial clustering technique for low-resolution facial dataset obtained from video surveillance footage with the help of HAAR cascade classifier. Different models like ResNet 50 and Inception ResNet V2 were used for feature extraction with weights pre-trained on ImageNet Dataset. Further, several combinations of Scaling and calculated Dimensionality Reduction techniques were applied before being fed into clustering algorithms and finally accuracy was calculated on obtained clusters.