Human-Object Interaction: Application to Abandoned Luggage Detection in Video Surveillance Scenarios

CCTV systems bring numerous advantages to security systems, but they require notable efforts from human operators in case of alarming events in order to detect the precise triggering moments. This paper proposes a system that can automatically trigger alarms when it detects abandoned luggage, detects the person that left the baggage and then tracks the suspicious person throughout the perimeter covered by a CCTV system. The system is based on Mask R-CNN and has been tested with several backbone configurations. Wee valuate each subsystem independently on datasets specific for their task. The network model proves to be robust enough to carry on all of the three different tasks as demonstrated by tests.

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