A Monitoring System for Supermarket Based on Trajectory of Palm

In this paper, a monitoring system that can distinguish the normal behavior from abnormal ones based on trajectory of palm for supermarket is designed. Our system brings some traditional algorithms and insights together to construct a framework for a new field called Supermarket Monitoring. In this project, only the moving hands are considered. To fulfill the automated monitoring task, the self-adaptive background subtraction technique and the YIQ skin color model are combined to detect the moving hands. In order to accurate localization at palm, a new method is developed. After successfully detecting the moving hands, a linear prediction model is cited to realize the object tracking. The Self-Organizing Map is used to distinguish normal behavior from abnormal ones by analyzing the trajectory characterizations of the moving hands. The experiment results show that this system is robust and effective.