Alert Generation on Detection of Suspicious Activity Using Transfer Learning

The system aims to give CCTV cameras the ability to detect suspicious activity, without human intervention. The goal of this paper is to identify suspicious activity for Surveillance and alert the shop owners when suspicious activity is detected. Electronic Article Surveillance (EAS) systems are widely used in today's retail stores, but this system is not capable enough as the shoplifters can easily remove the tag or label from the product. Hence, this system aims to take real-time videos from CCTV as an input and pass it to the CNN model created with the help of transfer learning and detect `Shoplifting', `Robbery' or `Break-In' in the store and notify it to the owners as soon as it occurs. Finally the main motive is to provide a system that detects suspicious activities without human intervention and generates alert, thus making a huge revolution in today's surveillance system.