REAL-TIME ANOMALY DETECTION USING VIDEO SURVEILLANCE FOR ENHANCING THE SECURITY

Computer Science & Engineering

For a real-time video surveillance system, AED (Anomalous Event Detection) is especially helpful in terms of safety as well as security. Today, monitoring objects and movement in low resolution video is a particularly challenging task due to the loss of specific viewpoint in the external appearance of moving objective article. Additionally, the demand has not been met by the number of strangeness kinds that real-time machine checking could detect. The identification of abnormalities is extremely important and usually becomes absolutely necessary in high-risk situations. When the system discovers or detects any unexpected or anomalous actions while video surveillance is being conducted in real-time, alerts are generated. The suggested remedy may also be used by any source and doesn't require a high limit of capacity structure to achieve the best outcome. The arrangement also includes a simple but sophisticated approach to deal with the rapid alerting and anomaly detection framework of today. Object recognition and tracking, which is widely employed in many industries such as medical care observation, autonomous driving, irregularity identification, and so forth, is one of the most important and difficult fields in computer vision. Due to its numerous practical applications in various domains, including event analysis, human-computer interaction, crowd analysis, video surveillance, behavior analysis, etc., the tracking of moving objects in movies has been extensively explored during the past 20 years. We can satisfy the requirements to give the citizens of the nation the essential security with the use of machine learning algorithms. Additionally, we can somewhat reduce the global crime rate. Nowadays, it is extremely dangerous to walk down the street, even in broad daylight, so the proposed system will help to reduce all anomaly activities.

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