Skip to main content
CASE STUDY DOCUMENT2025

Facelogix

High-performance facial authentication and security platform utilizing advanced facial embedding distance.

Timeline2025
Reading Time1 min read
External Links
PythonPyTorchInsightFaceFastAPIRedisSQLite
――

Context & Problem

Biometric security gates often struggle with static photo bypass attacks or experience network latency lags during peak login times. Facelogix is a high-performance local gateway providing hardware-efficient verification combined with liveness detection.

Architecture

System pipeline layout representing coordination blocks and execution pathways designed for this solution.

LOCAL NETWORKEdge HardwareIP Security CameraContinuous RTSP StreamH.264 / 1080pPhysical Gate RelayGPIO ActuatorAuth Signal ReceiverRTSP VideoTrigger SignalCentral Compute ServerFastAPI OrchestratorJob Queueing & Real-time WebsocketsInsightFacePyTorch FaceNet512D EmbeddingsAnti-SpoofingOptical Flow ModelsLiveness DetectionRedis In-MemoryVector CacheSQLite StorageAudit Logs

Implementation

  • Integrated the InsightFace embedding extractor running local PyTorch inference.
  • Implemented real-time liveness detection based on optical flow and face landmark eye-closure indices.
  • Created an in-memory Redis lookup index mapping facial embeddings, bypassing standard database table queries.

Challenges & Trade-offs

CHALLENGE: Bypasses using printed high-resolution photo sheets.

RESOLUTION: Engineered a Fourier transform texture analyzer evaluating frequency details of surface reflection, stopping flat-paper reflection attacks.

Results & Impact

Quantitative metrics and verified outcomes obtained from benchmarks.

99.2%Verification Accuracy
sub-200msGateway Latency
98.9%Liveness Check Precision

Faizal Shaikh

AI & ML Engineer · Mumbai, India

✦

© 2026 Faizal Shaikh. All rights reserved.