Missing person cases are a global concern that cause emotional distress for families and challenges for law enforcement agencies. Traditional search methods such as posters, manual surveillance, and public announcements are slow and inefficient. This paper proposes FaceTrace, an artificial intelligence based missing person detection system that uses deep learning facial recognition to identify individuals from images and surveillance streams. The system leverages ArcFace embeddings, computer vision techniques, and a centralized MySQL database to match uploaded images with stored records. The proposed system enables faster identification and improves accuracy compared to manual methods.
Patil et al. (Thu,) studied this question.
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