Detecting and tracking of multiple moving objects for intelligent video surveillance systems

Computer Vision is the part of “Artificial Intelligence” concerned with the theory behind artificial systems that extract information from images. Within which, Video Surveillance is a term given to monitor the behavior of any kind through videos. It requires person to monitor the CCTV and huge volume of memory to record it. One of the major challenges involved is the huge volume of video storage and retrieval of the same on demand. In order to avoid the depletion of human resources and to detect the suspicious behaviors that threaten safety and security, Intelligent Video Surveillance system (IVS) is required. The proposed work is focused on bringing effective and efficient video surveillance system with added intelligence to avoid human intervention in identifying security threats. In IVS, Extended Kalman filters the Gaussian mixture models are used to detect the moving objects. A tracking algorithm is proposed for tracking the moving objects. It implements position of each group, the recognition of the same group, and the newly appearing and disappearing groups. So, the proposed work IVS, promises the robustness against the environmental influences and speed, which are suitable for the realtime surveillance in detecting and tracking moving objects.