FACEFIND AI: AN AI-BASED MISSING PERSON IDENTIFICATION SYSTEM

Author

P.ANIS FATHIMA, Dr. K.MERRILIANCE

Abstract

 The increasing number of missing person cases has become a major public safety concern, highlighting the need for faster and more efficient identification methods. Traditional approaches rely on manual verification and continuous monitoring of CCTV footage, making the process time-consuming and prone to human error. To address this challenge, this project proposes FaceFind AI, an intelligent missing person identification system that utilizes Artificial Intelligence, Deep Learning, and Computer Vision for real-time facial recognition. The system integrates the YOLOv11 object detection algorithm to detect faces from live CCTV video streams and the FaceNet model to extract facial embeddings and match them against a centralized database of registered missing persons. Upon successful identification, the system generates an instant alert with relevant details such as identity, confidence score, timestamp, camera location, and captured image, while maintaining a log for future investigation. The proposed solution aims to reduce manual effort, improve the accuracy and speed of missing person identification, and enhance the efficiency of search and rescue operations. It can be effectively deployed in public places such as airports, railway stations, shopping malls, hospitals, educational institutions, and smart city surveillance networks to strengthen public safety and support law enforcement agencies.

Keywords

Missing person identification system, AI missing person locator, AI facial recognition software, Biometric facial recognition, Automated facial matching, Computer vision for law enforcement

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References

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