Real-time Smart Situation Awareness based on Camera Array and Machine Learning

Abstract

This paper proposes a real-time situation awareness system based on a surveillance camera array and machine learning techniques. The surveillance camera array consists of multiple PTZ cameras which are divided into two classes: large area cameras and local area cameras. Large area cameras are used to detect whole moving targets (e.g. persons, cars) and local area cameras are used to detect a specific area of the moving targets (e.g. person faces, car license plates). The behaviors of the detected moving targets are recognized to be normal or abnormal by combining shortterm and long-term video sequence analyses. Furthermore, the detected faces are fed to a face recognition subsystem to determine whether the person is known or not. The experimental results show the proposed situation awareness system is effective and useful.