Simulink Model for Object Tracking using Optical Flow

Object tracking and detection is first step in applications such as video surveillance. The main aim of object tracking has been developed to estimate location, velocity and distance parameters of moving objects with the help of static camera. Object tracking system requires accurate segmentation of objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Optical flow allows multiple moving targets to be separated based on their individual velocities; optical flow techniques are prone to errors caused by changing lightning and occlusions, both common in surveillance environment. In this paper we propose a combined motion segmentation/optical flow algorithm for used in object tracking. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects.