FaceLink
Team consisting of three full‑stack developers (Python/Django, React, JWT, WebSockets, Celery, AWS), led by Raseena Anwar (B.Tech—Mohandas College; ex‑Brototype), building scalable web apps.
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Project Description
FaceLink is an AI-powered solution designed to address the real-world problem of locating missing persons in crowded places like malls. Each year, many individuals—especially children and the elderly—go missing in such environments, and traditional methods of searching often prove slow and ineffective. FaceLink offers a real-time solution by scanning live video feeds from IP or CCTV cameras to detect and match faces against a reference image provided by the user. This not only enhances the speed of recovery but also provides significant support to families and security personnel.
The technology stack includes HTML, CSS for the frontend interface, Django REST Framework for backend services, and Python libraries like OpenCV and Dlib for facial recognition. Live video is streamed through IP cameras and processed in real time. Couchbase Capella serves as the primary database for storing facial data and embeddings, ensuring high-speed data access and reliability