Particle-filter-based intelligent video surveillance system

Abstract

In this study, an intelligent video surveillance (IVS) system is designed based on the particle filter. The designed IVS system can gather the information of the number of persons in the area and hot spots of the area. At first, the Gaussian mixture background model is utilized to detect moving objects by background subtraction. The moving object appearing in the margin of the video frame is considered as a new person. Then, a new particle filter is assigned to track the new person when it is detected. A particle filter is canceled when the corresponding tracked person leaves the video frame. Moreover, the Kalman filter is utilized to estimate the position of the person when the person is occluded. Information of the number of persons in the area and hot spots is gathered by tracking persons in the video frame. Finally, a user interface is designed to feedback the gathered information to users of the IVS system. By applying the proposed IVS system, the load of security guards can be reduced. Moreover, by hot spot analysis, the business operator can understand customer habits to plan the traffic flow and adjust the product placement for improving customer experience.

Particle-Filter-Based Intelligent Video Surveillance System

“…Moreover, it is not economically worthwhile to hire multiple security guards to monitor one video surveillance system. Therefore, intelligent video surveillance (IVS) systems have become more and more important in commercial sector and have attracted a lot of attention in research area as well [1][2][3].…”

“…After the object of interest is detected, the goal is to analyze their behavior that sometimes can be done by tracking them. Usually, particle filters and Kalman filters are employed for the purpose of tracking objects in IVS systems [6][7][8][9][10].…”