A machine learning based solution to detect shoplifting and other anomalies in human behavior using existing surveillance camera systems in shops and public facilities.

Key features:

• Real-time monitoring of human behavior to identify anomalies.
• Comparison of observed behavior with known patterns of theft, robbery, and stealing.
• Automatic alert system to notify security personnel of suspected shoplifting incidents.

The system successfully detects anomalies in behavior, classifies them into different types (e.g., shoplifting, stealing, robbery), and effectively protects retail businesses from financial losses caused by shoplifting.