A Review of Latest Trends and Technologies in the Field of Facial Re-recognition in Surveillance Cameras

Abstract

Deep Learning-driven advances in facial re-identification are transforming computer vision. The increasing need for precise identity identification in surveillance, law enforcement, and public safety is being met by this advancement. Complex face feature extraction is automated by Deep Learning, particularly with Convolutional Neural Networks (CNNs), improving recognition under difficult circumstances. This paper focuses on the most recent developments and the influence of Deep Learning on facial re-identification. For scholars, practitioners, politicians, and industry actors, it's a vital resource that emphasizes the need of staying current for the best possible system use. To sum up, the combination of Deep Learning with facial re-identification offers accurate, dependable, and effective identity recognition. It is essential for security, law enforcement, and public safety that technology advances.