Multi-Camera Person Tracking And Left Luggage Detection Applying Homographic Transformation

Today video surveillance systems are widely used in public spaces, such as train stations or airports, to enhance security. In order to observe large and complex facilities a huge amount of cameras is required. These create a massive amount of data to be analyzed. It is therefore crucial to support human security staff with automatic surveillance applications, which will create an alert if security relevant events are detected. This way video surveillance could be used to prevent potentially dangerous situations, instead of just being used as forensic instrument, to analyze an event after it happened. In this treatise we present a surveillance system which supports human operators, by automatically detecting abandoned objects and loitering people. Two major parts have been implemented: a multi-camera tracking algorithm based on homographic transformation and the subsequent analysis of the observed object trajectories. An alarm event is triggered if an object is abandoned for 25 seconds or a person is staying in the view for more than 60s.