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Object tracking is an interesting and needed procedure for many real time applications. But it is a challenging one, because of the presence of challenging sequences with abrupt motion, drastic illumination change, large pose variation, occlusion, cluttered background and also the camera shake. This paper presents a novel method of object tracking by using the algorithms spatiotemporal Markov random field (STMRF) and online discriminative feature selection (ODFS), which overcome the abovedoi:10.15623/ijret.2014.0304054 fatcat:qj5opqczsvafli4wptvs7m3zqq