Multi-camera tracking for smart video surveillance (original) (raw)

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 real-time surveillance in detecting and tracking moving objects.

Features-Based Moving Objects Tracking for Smart Video Surveillances: A Review

International Journal on Artificial Intelligence Tools

Video surveillance is one of the most active research topics in the computer vision due to the increasing need for security. Although surveillance systems are getting cheaper, the cost of having human operators to monitor the video feed can be very expensive and inefficient. To overcome this problem, the automated visual surveillance system can be used to detect any suspicious activities that require immediate action. The framework of a video surveillance system encompasses a large scope in machine vision, they are background modelling, object detection, moving objects classification, tracking, motion analysis, and require fusion of information from the camera networks. This paper reviews recent techniques used by researchers for detection of moving object detection and tracking in order to solve many surveillance problems. The features and algorithms used for modelling the object appearance and tracking multiple objects in outdoor and indoor environment are also reviewed in this pa...