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Extracting Motion Model Parameters with Robust Estimation

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2667))

Abstract

We propose a model parameter estimation algorithm from block motion vectors for extracting accurate motion information with the assumption that the undergoing motion can be characterized by an affine model. The motion may be caused either by a moving camera or a moving object. The proposed method first extracts motion vectors from a sequence of images by using size-variable block matching. It then processes them by using the adaptive robust estimation to estimate model parameters. Experimental results show that our approach is very effective in extracting model parameters.

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References

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© 2003 Springer-Verlag Berlin Heidelberg

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Jang, SW., Pomplun, M., Kim, GY., Choi, HI. (2003). Extracting Motion Model Parameters with Robust Estimation. In: Kumar, V., Gavrilova, M.L., Tan, C.J.K., L’Ecuyer, P. (eds) Computational Science and Its Applications — ICCSA 2003. ICCSA 2003. Lecture Notes in Computer Science, vol 2667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44839-X_67

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  • DOI: https://doi.org/10.1007/3-540-44839-X_67

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40155-1

  • Online ISBN: 978-3-540-44839-6

  • eBook Packages: Springer Book Archive

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