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Facial Recognition

Services/Computer Vision & Biometrics/Facial Recognition

Computer Vision & Biometrics

Facial Recognition

High-accuracy face detection and recognition using YOLOv8n-face and MobileFaceNet embeddings, enabling biometric attendance tracking and access control with on-device processing.

By the Numbers

99.2%

Recognition Accuracy

200ms

Verification Speed

10K+

Enrolled Faces

0.1%

False Acceptance Rate

How It Works

Implementation Process

01

Enrollment & Database Setup

We capture reference face images for all authorized individuals and generate their embedding vectors. The face database is securely stored with encryption and access controls.

02

Model Optimization

YOLOv8n-face and MobileFaceNet models are quantized and optimized for your target hardware. TFLite conversion ensures maximum performance on mobile devices and edge cameras.

03

Integration & Deployment

The recognition system is integrated with your attendance software, access control hardware, or mobile app. APIs connect face events to your existing business workflows.

04

Calibration & Monitoring

Recognition thresholds are calibrated to balance security and usability. Ongoing monitoring tracks false acceptance and rejection rates, with periodic model updates for new enrollees.

What We Deliver

YOLOv8n-Face Detection

Real-time face detection optimized for speed and accuracy using YOLOv8 nano architecture. Handles multiple faces simultaneously with bounding box precision even in challenging lighting.

MobileFaceNet Embeddings

Compact yet powerful face embeddings that encode identity into numerical vectors. MobileFaceNet delivers recognition accuracy rivaling larger models while running efficiently on mobile devices.

On-Device TFLite Inference

Models run locally on the device via TensorFlow Lite, ensuring zero-latency recognition without internet dependency. Biometric data never leaves the device, enhancing privacy and speed.

Attendance Tracking

Automated check-in/check-out via face recognition replaces manual sign-in sheets. Timestamps, photos, and confidence scores are logged for every attendance event.

Biometric Access Control

Secure facility access using face verification at entry points. Authorized personnel are recognized in real time, while unregistered faces trigger alerts and are denied entry.

Anti-Spoofing Protection

Liveness detection prevents spoofing with printed photos or screen displays. Multiple verification checks ensure only real, present individuals pass the recognition pipeline.

Use Cases

Recognition Applications

1

Workplace Attendance

Employees check in by simply looking at a tablet mounted at the entrance. The system logs their arrival time, eliminates buddy punching, and feeds data directly into payroll.

2

Secure Facility Access

A corporate office uses facial recognition at restricted areas instead of keycards. Only authorized personnel gain access, with every entry and denied attempt logged for security audit.

3

Child Pickup Verification

A childcare center verifies the identity of adults picking up children using face recognition. Only pre-registered guardians are allowed to complete the pickup, adding an extra layer of safety.

Technology Stack

YOLOv8n-faceMobileFaceNetTFLiteFlaskDockerCloud Run

Industries we serve with this

Education & Childcare→
Real Estate→

FAQ

Frequently asked questions

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What Is Facial Recognition and How Does It Work?

Facial recognition is a biometric identification technology that analyzes the unique features of the human face to authenticate or identify individuals. The process starts with face detection in an image or video stream, followed by the extraction of embeddings: numerical vectors that represent facial geometry with high fidelity. These embeddings are compared against a database using two modes: 1:1 verification, which confirms whether a person is who they claim to be, and 1:N identification, which searches for an individual across multiple records. At AISDC we implement this pipeline using YOLOv8n-face for detection and MobileFaceNet for embedding generation, resulting in a facial recognition system that is robust, fast, and suited for real-world business environments.

Business Use Cases for Facial Recognition

A facial recognition system unlocks concrete possibilities across multiple sectors. In manufacturing and corporate settings, facial access control eliminates cards and PINs, restricting critical areas to authorized personnel only. Facial recognition attendance automates contactless clock-in and clock-out, eliminating buddy-punching fraud. In daycares and schools, it enables safe student arrival registration and real-time notifications to parents. The retail sector uses biometric identification for loss prevention and customer flow analytics. In security facilities, the system operates 24/7 for perimeter monitoring. Every integration is adapted to the company's operational workflow without forcing radical changes to existing infrastructure, making adoption straightforward and minimally disruptive.

Accuracy, On-Device Processing, and Privacy

The models we use, optimized in TFLite format, run directly on the computing device or embedded hardware without sending images or biometric data to external servers. This on-device approach drastically reduces latency and eliminates the exposure of sensitive data in transit. In terms of accuracy, MobileFaceNet delivers high-quality facial discrimination even under variable lighting conditions. From a legal standpoint, biometric data processing in Mexico is governed by the LFPDPPP; accordingly, we design consent flows, privacy notices, and data deletion mechanisms in compliance with that law. Privacy is not an afterthought: it is built into the system architecture from the very first day of the project.

How We Integrate Facial Recognition Into Your Operation

Integration begins with a technical assessment: available camera types, lighting conditions, operating distance, and existing systems such as ERP, access control, or payroll platforms. We develop connectors so the facial recognition system communicates with your current infrastructure via API or shared database. We include anti-spoofing modules to reject deception attempts using photographs or screens. Deployment can run on compact hardware — mini-PCs, NPU-accelerated Raspberry Pi, or embedded Android devices — keeping infrastructure costs low. We provide an administration panel to manage profiles, audit access events, and generate reports. Our involvement does not end at delivery: we offer ongoing support, model updates, and fine-tuning based on each client's specific operational environment.

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