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Modelling and Simulation in Engineering
Volume 2016 (2016), Article ID 2592368, 8 pages
Research Article

An Adaptive Object Tracking Using Kalman Filter and Probability Product Kernel

Faculty of Sciences Rabat GSCM-LRIT Laboratory Associate Unit to CNRST (URAC 29), Mohammed V University, BP 1014, Rabat, Morocco

Received 13 September 2015; Revised 14 January 2016; Accepted 16 February 2016

Academic Editor: Aiguo Song

Copyright © 2016 Hamd Ait Abdelali et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We present a new method for object tracking; we use an efficient local search scheme based on the Kalman filter and the probability product kernel (KFPPK) to find the image region with a histogram most similar to the histogram of the tracked target. Experimental results verify the effectiveness of this proposed system.