Abstract
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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Wu, CF., Lin, CJ., Shiue, YJ., Lee, CY. (2012). Digital Image Stabilization Using a Functional Neural Fuzzy Network. In: Gaol, F., Nguyen, Q. (eds) Proceedings of the 2011 2nd International Congress on Computer Applications and Computational Science. Advances in Intelligent and Soft Computing, vol 144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28314-7_31
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DOI: https://doi.org/10.1007/978-3-642-28314-7_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28313-0
Online ISBN: 978-3-642-28314-7
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