Detection of unusual events in low resolution video for enhancing ATM security and prevention of thefts

In present-day applications, tracking object in low resolution video is a stimulating task due to loss of distinctive aspect in the visual outward look of moving target object. The present-day approaches are typically involved on the enhancement of Low Resolution (LR) video by super resolution techniques. However these approaches need massive computational cost. This cost again rises if we are handling with event detection. Recently, an algorithm has been developed which is capable of detecting unusual events and for enhancement of ATMs security where simple low resolution cameras are used because of their lower cost. Our state-of-the-art technique is able to detect the existence of unusual events like face masking, camera masking, fight or overcrowding in the low resolution video merely by means of standard deviation, statistical method of moving target objects. It is sufficient because it processes low resolution frames and also sends alert messages to the concerned authorities in investigation (surveillance) system for enhancing the ATMs security and prevention of thefts using conventional camera of low resolution.