TraceFusion: Precision AI for Missing and Wanted Person Detection
Year: 2025
Type: article
Abstract: With the advent of advanced technologies, which has paved the way for critical social challenges. One such social challenge is the identification of missing and wanted individuals in day-to-day basis. Manual identification is time consuming and less efficient to tackle this challenge.TraceFusion leverages Machine Learning(ML) to enhance efficiency in identification. The system features a Web based application that allows its users to register missing persons with image uploads,facilitating real time searches.The MTCNN model and the InceptionResNetV1 model processes live camera feeds as well as recorded videos to match faces against a database of missing and wanted persons which upon detection can assist the authorities in response actions. A flask based server performs real-time face recognition, while Firestore is used to store and retrieve images for matching. Using TraceFusion, public safety can be enhanced and investigations be fastened up.Index Terms—Face Recognition, Missing Person Detection, Wanted Person Identification, Artificial Intelligence, Machine Learning, MTCNN, InceptionResNetV1, Firestore, Flask.
Author: Linsa Mathew, Jifith Joseph, George P Kurias, Gokul Krishna AU, Sharunmon R, Amal Jyothi College of Engineering
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893311362
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