Paper Title
Smart Surveillance System

Smart video-surveillance systems are a powerful tool applied in varied scenarios with the aim of automating the detection of different risk situations and helping human security officers to take appropriate decisions in order to enhance the protection of assets. In this paper, we propose a complete expert system which focuses on the real-time detection of potentially suspicious behaviour in various environments. Our video-surveillance methodology contributes several innovative proposals that compose a robust application which is able to efficiently detect and track the trajectories of people and to discover questionable actions in any desired environment. As a first step, our system applies an image segmentation to locate the foreground objects in scene. In this case, the most effective background subtraction algorithms of the state of the art are compared to find the most suitable for our expert video-surveillance application. After the segmentation stage, the detected blobs may represent full or partial people bodies, thus, we have implemented a novel blob fusion technique to group the partial blobs into the final human targets. Then, we contribute an innovative tracking algorithm which is not only based on people trajectories as the most part of state-of-the-art methods, but also on people appearance in occlusion situations. Finally, the resultant trajectories of people obtained in the tracking stage are processed by our smart video-surveillance system for analyzing human behaviour and identifying potential abnormal situations such as loitering and jumping over fences of private territories. Furthermore, the notifications given off by our application in the form of emails are evaluated on a naturalistic private dataset, where it is evidenced that our smart video-surveillance system can effectively detect suspicious behaviour with a low computational cost in any given environmental context. Human monitoring of surveillance video is a very labour-intensive task. Detecting multiple activities in real-time video is difficult in manual analysis. Thus we have proposed this intelligent video surveillance system in which the analytics software processes video flow images to automatically detect objects and people and notify about the event of interest for security purposes. Our smart video surveillance system also detects situations in video flow that represent a security threat and trigger an alarm. This smart video surveillance system can be used in shopping centres, public places, banking institutions, companies, ATM machines, private houses and hospitals as well. In our smart video surveillance system we propose a system which analyses activity in the monitored space in real time and generates alarms by sending notifications to the authorities. Keywords - Surveillance system, Detection, Tracking, Behaviour analysis, Notifications