Abandoned or removed object detection from visual surveillance: a review

Abstract

Intelligent Visual Surveillance is an important and challenging research field of image processing and computer vision. To prevent the ecological and economical losses from bomb blasting, an intelligent visual surveillance is required to keep an eye on public areas, infrastructures and discriminate an unattended object left among multiple objects at public places. An unattended object without its owner since a long time at public place is considered as an abandoned object. Identification of an abandoned object on real-time can prevent the terrorists attack through an automated video surveillance system. In recent decade, a good number of publications have been presented in the field of intelligent visual surveillance to identify the abandoned or removed objects. Furthermore, few surveys can be seen in the literature for the various human activity recognition but none of them focused deeply on abandoned or removed object detection in a review. In this paper, we present the state-of-the-art which demonstrates the overall progress of abandoned or removed object detection from the surveillance videos in the last decade. We include a brief introduction of the abandoned object detection with its issues and challenges. To acknowledge to the new researchers of this field, core technologies, and frequently used general steps to recognize abandoned or removed objects have been discussed in the literature such as foreground extraction, static object detection based on non-tracking or tracking approaches, feature extraction, classification and activity analysis to recognize abandoned object. The objective of this paper is to provide the literature review in the field of abandoned or removed object recognition from visual surveillance systems with its general framework to the researchers of this field.