An integrated schema for efficient face recognition in social networking platforms

Abstract

The conceptual background of face recognition (FR) evolved witnessing various contributions in the past two decades which has been extended towards a wide area of applications including commercial and law enforcement security solutions both. However, it has become a foundation of several breakthroughs on various research aspects associated with cloud computing (CC) driven big data analytics and machine learning platforms. The extended research track in this specific domain claimed to transform the conventional view of solving the problems associated with analytics based FR in social media platforms. The study also aimed to explore various scope of integrating conventional social media (SM) based big data analytics (BD) technology on FR considering an approach of machine learning (ML). Thereby it has formulated a novel framework well capable of face detection considering a machine learning approach on a cloud operated SN platforms. The study formulated analytical approach namely computationally efficient face recognition (CE-FR) schema for face tagging on big data driven SN platforms. The effectiveness of the study further evaluated to validate the performance of the proposed FR system.