Object Detection and Tracking in Videos Using Snake and Optical Flow Approach

In real time situations, non rigid object tracking is a challenging and important problem. Due to the non rigid nature of objects in most of the tracking applications, deformable models are appealing in tracking tasks because of their capability and flexibility. The proposed approach uses an observation model based on optical flow information used to know the displacement of the objects present in the scene. After finding the moving regions in the initial frame, we are applying active contour model (ACM) to track the moving objects in the further frames dynamically. These models have been used as a natural means of incorporating flow information into the tracking. The formulation of the Active Contour Model by incorporating an additional force driven optical flow field improves the tracking speed. This algorithm efficiently works to track for low contrast videos like Aerial videos.