A Comprehensive Survey of Advanced Surveillance Techniques for Theft Detection in Retail Environments: Integrating Multi-Object Tracking and Human Pose Estimation

Abstract

This paper discusses recent advancements in theft surveillance techniques, including tracking multiple objects and estimating human movements. These technologies help with real-time monitoring, understanding behaviors, and ensuring public safety. The major computational challenges of the techniques have been looked at from different angles, including balancing accuracy with efficiency, occlusion management, and scalability in different environments. It also identifies areas that require further research and proposes potential future directions, such as incorporating diverse data types and developing compact and adaptable models. This work is meant to be a helpful tool for researchers and practitioners, giving them a look at the present status of these technologies and steering the creation of new smart systems