Abstract
We propose an adaptive robust estimation algorithm for filtering motion vectors. We first extract motion vectors from consecutive images by using size-variable block matching and then apply the extracted motion vectors to adaptive robust estimation to filter them. The proposed robust estimation defines a sigmoid weight function, and eliminates outliers by gradually tuning the sigmoid function to the hard limit as the error between model parameters and input data is minimized.
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© 2002 Springer-Verlag Berlin Heidelberg
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Jang, SW., El-Kwae, E.A., Choi, HI. (2002). Adaptive Robust Estimation for Filtering Motion Vectors. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds) Rough Sets and Current Trends in Computing. RSCTC 2002. Lecture Notes in Computer Science(), vol 2475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45813-1_74
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DOI: https://doi.org/10.1007/3-540-45813-1_74
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