Tracking of Missing Person Identification with Face Recognition Using Computational Ensembling Approach

Through the use of computational ensembling, this study outlines a unique framework with the purpose of enhancing the ability of face recognition technology to locate individuals who have gone missing. The research investigates the development of face recognition methods, databases, and technology throughout the course of time, taking into account both ethical concerns and practical applications of the field. Components of the technique include scalability, real-time processing, meticulous data collecting, attentive study of relevant literature, ensemble model construction, and data processing. The study’s positive results indicate the use of databases such as CASIA WebFace, Mega Face, MS-Celeb-1M, and VGGFACE2 and VGGFACE2. In addition to the research and development of face recognition technologies for use in real-life settings, the primary objective of this project is to find solutions to the critical problem of missing people throughout the globe.