Abandoned object detection with alert system

Visual Surveillance is one of the necessary research fields in Computer vision and image processing. Various techniques are developed to perform automated video surveillance. One of the critical challenges in surveillance is detecting abandoned objects in crowded places like parks, shopping complexes and airports, etc., to prevent ecological loss frombomb blasting, gun fires, lost baggage, etc. Closed Circuit Television (CCTV) continuously monitor public places and discriminate unattended and abandoned luggage from different objects. An abandoned thing in surveillance is nothing but an unattended object without a person for a long duration. Identifying these objects in real-time can help prevent bomb blasts and terrorist attacks etc. Many types of research have been performed and published in surveillance for abandoned object detection in recent years. Deep learning is one of the significant fields where various techniques and algorithms are developed for detecting unattended objects. Though these methods detect the objects significantly, they lack computational complexity. A classical edge detection method using Canny edge detection to overcome these challenges is developed to identify the abandoned objects in surveillance scenes.