Intelligent Video Surveillance based on Object Tracking

Tracking moving objects as along with their movement through video sequences is one of the most basic and most crucial tasks in computer vision. This serves as the foundation for numerous higher-level automated applications in numerous domains, including surveillance, augmented reality and motion capture in moving object detection. Object tracking is key element of an IVS system which can further be modeled for many suspicious activity detection systems. There are many approaches and proposed algorithms for object tracking, out of which mean shift algorithm is the basis of implementation of IVS in this paper. The work proposed in this paper was defined to meet following objectives: to create a video sequence for moving object tracking; to design an experimental set up for moving object detection; and, to design and implement moving object tracking algorithm, The proposed algorithm was implemented on a captured video sequence. Object was detected first according to the image input, and then tracked in subsequent frames. The experimental implementation could perform the object tracking without missing any frame and could successfully overlay bounding box. It could successfully generate an image sequence after the complete implementation of Mean Shift Algorithm. The performance of algorithm was checked by successfully tracking the user defined object and performing the overlay function in the identified object.