Detection of cigarette cabinet openings using surveillance camera footage and pre-trained VGG models: a supermarket case study

Abstract

Theft in supermarkets remains a significant challenge for retailers, leading to substantial financial losses. As a proof of concept, this study explores the application of Computer Vision (CV) for detecting the opening of cigarette cabinets in supermarkets by analyzing security camera footage. By identifying the status of the cabinet in an image as open, the proposed CV approach offers potential solutions to enhance security and reduce theft related product losses in supermarkets. This research serves as a proof of concept for automated surveillance and cabinet status detection in retail settings.