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Optical Flow Computation in the Presence of Spatially-Varying Motion Blur

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Advances in Visual Computing (ISVC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8887))

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Abstract

While most of the techniques for inferring optical flow are based on the brightness constancy assumption, various conditions including the presence of motion blur evidently violate this fundamental presumption. If the source image and the target image appear to be dissimilar due to different blur kernels, traditional methods will fail to achieve accurate results. We present a new method, MB-CLG, that considers constructing a new pair of blurred frames, followed by regular optical flow computation. The proposed method employs a coarse-to-fine approach, in conjunction with a smoothness matrix to account for occluded regions. Rather than warping frames or precomputing a large grid of derivatives, MB-CLG warps the flows at each iteration. This leads to lower computational cost, and requires less data storage. Based on the results for various sequences, MB-CLG outperforms existing optical flow methods in the sense of AAE, AEP and MSE.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064, USA

    Mohammad Hossein Daraei

Authors
  1. Mohammad Hossein Daraei
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada at Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. The University of Texas at Dallas, 75080, Richardson, TX, USA

    Ryan McMahan

  6. NextGen Interactions, 27604, Raleigh, NC, USA

    Jason Jerald

  7. Indiana University, 46202, Indianapolis, IN, USA

    Hui Zhang

  8. Microsoft Research, 1 Microsoft Way, 98052, Redmond, WA, USA

    Steven M. Drucker

  9. University of Delaware, 19716-2712, Newark, DE, USA

    Chandra Kambhamettu

  10. Intel Corp., 95054, Santa Clara, CA, USA

    Maha El Choubassi

  11. Computer Graphics and Interactive Media Lab, Department of Computer Science, University of Houston, 77004, Houston, TX, USA

    Zhigang Deng

  12. NVIDIA, 34788, Leesburg, FL, USA

    Mark Carlson

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© 2014 Springer International Publishing Switzerland

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Daraei, M.H. (2014). Optical Flow Computation in the Presence of Spatially-Varying Motion Blur. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8887. Springer, Cham. https://doi.org/10.1007/978-3-319-14249-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-14249-4_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14248-7

  • Online ISBN: 978-3-319-14249-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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