Building a Real-Time Shoplifting Detection System for US Retail
The multi-camera behavior analysis system provided by Eminent AI changed how we approach security. Being able to track people across cameras while detecting suspicious activity is a game-changer.
Revenue Loss From Shoplifting They Couldn't Stop in Time
A US-based retail client needed a smarter way to prevent theft across their stores. Manual monitoring was inconsistent and reactive — by the time staff noticed something, the loss had already happened.
They needed a system that could watch every camera, every frame, and flag suspicious behavior the moment it occurred.
What We Built
Person Detection
Identifies every person in frame across all cameras simultaneously in real time.
Shoplifting Detection
Detects suspicious behavior and theft actions the moment they occur with high confidence.
Action Recognition
Understands what each person is doing — walking, reaching, concealing — not just where they are.
Cross-Camera Tracking
Follows the same individual across multiple cameras using appearance matching, maintaining identity.
Pose Estimation
Reads body language and physical gestures to add behavioral context to each detection.
Real-Time Alerts
Flags shoplifting incidents instantly so staff can respond before the person leaves the store.
Impact & Results
Decreasing stock shrinkage through real-time AI security.
Near-instant identification of suspicious actions.
Scale-ready surveillance across national retail chains.
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