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Social Perspective of Suspicious Activity Detection in Facial Analysis: An ML-Based Approach for the Indian Perspective
Abstract
The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world via creating new services and applications in a variety of sectors such as environmental monitoring, mobile health systems, and intelligent transportation systems and so on. The information and communication technology (ICT) sector is experiencing significant growth in data traffic, driven by the widespread usage of smart phones, tablets, and video streaming, along with the significant growth of sensors deployments that are anticipated soon. This chapter describes suspicious activity detection using facial analysis. Suspicious activity is the actions of an individual or group that is outside the normally acceptable standards for those people or that particular area. In this chapter, the authors propose a novel and cost-effective framework designed for suspicious activity detection using facial expression analysis or emotion detection analysis in law enforcement. This chapter shows a face detection module that is intended to detect faces from a real-time video.
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