Evil and Fear Detection Using Facial Recognition Algorithms for Crime Prevention - A Survey
Ahmad Asnawi Ahmad Shukri, Lokman Mohd Fadzil · International Journal of Electrical and Electronics Engineering · 2024
The development of facial recognition technology has transformed a number of industries, including crime prevention and law enforcement. This work proposes a revolutionary method for improving crime prevention through the creation of a facial recognition system that can identify expressions linked to fear and malevolent intent. A model is being proposed to recognize minor facial cues suggestive of evil intentions and terror responses by utilizing deep learning techniques and a large dataset. With the use of face cues, including micro-expressions, eye movements, and muscular contractions, the proposed system is able to discriminate between people who are exhibiting such emotions. The system can be used for a wide range of purposes, such as real-time surveillance in public areas and witness and suspect identification to support investigations. However, when using such technology, privacy, ethics, and the possibility of prejudice issues need to be properly considered. The development, validation, and possible societal ramifications of the algorithm are covered in this paper, with a focus on the necessity of finding a balance between technical advancement and defending individual liberties and rights. The research aims to further the ongoing discussion on the appropriate application of facial recognition technology in public safety and crime prevention.