The object tracking is critical to visual / video surveillance, analysis of the activity and gesture recognition. The major difficulties to be occurred in the visual tracking are different environmental conditions, illumination changes, occlusion and appearance. In this paper, the comparative analysis of the different systems which are used to recognize the head gestures under different environmental conditions is discussed. The existing algorithm used to recognize the head gestures has some limitations. The existing algorithm cannot work under outdoor environmental conditions. The traditional camshift algorithm and unscented kalman filter are integrated and used to recognize the head gestures under outdoor environmental conditions. The unscented kalman filter is a tracking algorithm used to remove the limitations of the traditional camshift algorithm. The simulation result shows the better performance of the improved algorithm than the traditional camshift algorithm.
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