Detection of Abandoned Objects in Public Places

Abstract

Video surveillance in public places has witnessed tremendous growth over the last decade with applications based on closed-circuit security systems to IP cameras. Among the various aspects of surveillance, automatic detection and classification of abandoned objects could serve as a valuable application reducing potential threats to public safety. The aim of this project is to detect the unattended abandoned objects from videos of public places. The developed system relies on background subtraction from the video stream and segment out foreground objects. Humans are then detected from the foreground objects and are distinguished from the static foreground objects. The owner of a static baggage object is assumed to be the nearest human attending it. The owner is tracked and if abandons the baggage for more than a predefined time the baggage is considered abandoned and an alarm is generated. The proposed system is evaluated on videos from the benchmark PETS database as well as a custom developed database and realized promising performances.