This study proposed a real-time video stabilization method to eliminate the unwanted shakes, preserve the intended panning of camera, and improve the stability of the captured video sequence. The proposed method uses a functional neuro-fuzzy network to learn the phenomena of different shakes and then it chooses adequate compensation weight for two different methods to calculate the compensated motion vector. Experimental results show that the proposed method has superior performance than other motion compensation methods.
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