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Visual tracking is still a challenging problem in computer vision. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. In this work, we propose a new method to track arbitrary objects using both sum-ofsquared differences (SSD) and color-based mean-shift (MS) trackers in the Kalman filter framework. The SSD and the MS trackers complement each other by overcoming their respective disadvantages. The rapid model change in SSD tracker isdoi:10.1109/icip.2005.1529851 dblp:conf/icip/BabuPB05 fatcat:5jujuayz3jhk3hbfgldmri55py