Developer Details Production-Ready Face Recognition Pipeline with Anti-Spoofing

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A software engineer has published a technical walkthrough on building a production-grade face recognition system designed for deployment on devices like Android tablets in industrial settings. The pipeline combines a lightweight RFB-320 face detection model, anti-spoofing checks to block print and replay attacks, and FaceNet-style 128-dimensional embeddings for identity matching. HNSW indexing enables sub-millisecond matching across databases of over 10,000 enrolled users, while a dynamic threshold adjustment method reportedly reduces false acceptances by around 30%. The system uses thread-safe ONNX inference running three models sequentially and supports offline, RSA-licensed deployment for factories, mines, and remote sites. The author also documents real-world challenges encountered during development, including channel order bugs, semaphore starvation, and cold start latency issues.

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