Kernel based Object Tracking using Color Histogram Technique

Object tracking is the process of locating moving objects in the consecutive video frames. Real time object tracking is a challenging problem in the field of computer vision, motion-based recognition, automated surveillance, traffic monitoring, augmented reality, object based video compression etc. In this paper kernel based object tracking using color histogram technique has been applied for different challenging situations. Covariance tracking algorithm has also been applied to the same problem. From the simulation studies it is clear that this two techniques effectively handle various challenges like occlusion, illumination changes etc. Experimental results reveal that the histogram based method is efficient in terms of computation time and covariance tracker is better in terms of detection rate.