Bandwidth-adaptive tracking algorithm based on Mean Shift and Kalman prediction
Biao Wang · Computer Engineering and Science · 2013
As a widely used traditional tracking technique in visual surveillance , Mean Shift algorithm has a deficiency in handling moving targets with high speed or large scale change.In order to sove this problem , a bandwidth-adaptive tracking algorithm based on Mean Shift and Kalman prediction was proposed.The algorithm uses Kalman filter to predict the positions of fast moving objects in the successive frame , which are as the initial positions for Mean Shift iteration.Bandwidth trials is utilized to adjust the bandwidth automatically for targets'scale change.The experimental results of pedestrians and vehicle tracking show that our algorithm is effective and robust.