Leveraging Facial Analytics for Enhanced Crime Prevention - Integrating Video Surveillance and FaceNet Algorithm

Facial analysis in crime prevention aims to leverage technologies like FaceNet and MTCNN algorithms for various objectives, including registering criminals into databases, matching photos to identify suspects, and enhancing video surveillance for real-time monitoring and detection of criminal activity. This research investigates the efficacy of integrating FaceNet algorithm within existing video surveillance infrastructure. These techniques enable law enforcement agencies to effectively utilize facial recognition technology in identifying and apprehending individuals involved in criminal activities, thereby enhancing public safety and crime prevention efforts.