Abandoned/removed object detection in video surveillance systems
Muhammed Kalabalik, Fikret Alim, Cevahir Çığla · 2024
Abandoned/removed object detection is a critical task in video surveillance systems for ensuring public safety and security. In these type of systems, mostly static cameras are utilized to monitorize and observe the surrounding, hence background modeling based techniques are suitable for detection of objects that produce obvious changes in the image content. GMM(Gaussian Mixture Model) is one of the most endeavoured modeling technique for real-time surveillance applications. In this paper, we propose an edge-based approach for the detection of abandoned or removed objects under static background assumption. Traditional edge-based approaches rely on the amount of edge energy that suffers in cluttered areas. In order to solve this problem, we extend edge energy by use of edge orientation between current and background frame along foreground object's edge contours. This approach increases the robustness of abandoned/removed classification which is supported by detailed experiments.