/portfolio

Face Recognition at Events

Scope:

Automating face recognition for event photography using AI

Industry:

Media / Entertainment

Customer:

Access Management Company for Events & Schools (NDA)

Timeline:

6 month for POC project

Team

Computer Vision and ML Engineers

DevOps Engineer

QA Engineer

Business Analyst

Project Manager

Key technologies

Android

AWS

Azure

Kairos API

OpenCV

Problem

Manual face/attendee identification was often a bottleneck at high-throughput events

GOAL

Develop an AI-powered solution to automate detection labeling, and storage of attendee information

SOLUTION

Photo capture via cameras or gallery upload
Automated labeling
Ability to edit attendee details

Impact

Efficiency gain of 60-80%

Faster and more efficient identification

45-55% boost in face recognition accuracy

Optimized for high-volume, real-time photo processing

50-70% time savings on manual identification

Reduced operational expenses through automation