Client
Private Client
Timeline
End-to-end delivery
Built by
thehsquares
Project Overview
A custom computer vision system that detects faces in live video streams and images, extracts embeddings, and matches identities against an enrolled database — delivered for private, on-premise use without a public-facing product URL.
The Challenge
The client needed reliable face detection and recognition under varied lighting, angles, and camera quality — with low false positives, fast inference, and a pipeline that could run on their own infrastructure without exposing data to third-party SaaS APIs.
Our Solution
We engineered an end-to-end CV pipeline: face detection, alignment, embedding extraction, similarity matching, and a secure API layer for enrollment and verification — optimized for real-time performance and private deployment.
Our Approach
Model Selection & Tuning
Evaluated detection and recognition architectures for accuracy vs. latency on target hardware.
Pipeline Engineering
Built preprocessing, embedding, and matching stages with configurable confidence thresholds.
Private Deployment
Packaged the system for on-premise delivery with API endpoints and enrollment workflows.
Services Delivered
Key Deliverables
- Real-time face detection module
- Recognition & identity matching engine
- Secure enrollment API
- Performance benchmarking report
- Deployment documentation
Key Features Built
- Multi-face detection in images and video streams
- Embedding-based identity matching with threshold control
- Enrollment and gallery management for known identities
- Low-latency inference optimized for production hardware
- Private deployment — no public live demo URL
Impact & Results
- Delivered a production-ready face recognition pipeline for private use
- Reduced manual identity verification overhead for the client
- System runs entirely on client-controlled infrastructure
- Extensible foundation for access control and analytics use cases
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