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Large Parallax Image Stitching Using an Edge-Preserving Diffeomorphic Warping Process

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11182))

Abstract

Image Stitching is a hard task to solve in the presence of large parallax in video frames. In many cases, video frames shot using hand-held cameras have low resolution, blur and large parallax errors. Most recent works fail to align such a sequence of images accurately. The proposed method aims to accurately align image frames, by employing a novel demon-based, edge-preserving diffeomorphic registration for image stitching, termed as “DiffeoWarps”. The first stage aligns the images globally using a mesh-based perspective (homography) transformation. At the second stage, an alternating method of minimization of correspondence energy and TV-regularization improves the alignment. The “diffeowarped” images are then blended to obtain good quality stitched results. We experimented on two standard datasets as well as on a dataset comprising of 10 sets of images/frames collected from unconstrained videos. Both qualitative and quantitative performance analysis show the superiority of our proposed method.

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Author information

Authors and Affiliations

  1. V.P. Lab, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India

    Geethu Miriam Jacob & Sukhendu Das

Authors
  1. Geethu Miriam Jacob
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  2. Sukhendu Das
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Corresponding author

Correspondence to Geethu Miriam Jacob .

Editor information

Editors and Affiliations

  1. DGA, Bagneux, France

    Jacques Blanc-Talon

  2. Laboratoire XLIM, Futuroscope Chasseneuil Cedex, France

    David Helbert

  3. Ghent University, Ghent, Belgium

    Wilfried Philips

  4. CSIRO-ICT Centre, Canberra, ACT, Australia

    Dan Popescu

  5. University of Antwerp, Wilrijk, Belgium

    Paul Scheunders

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Jacob, G.M., Das, S. (2018). Large Parallax Image Stitching Using an Edge-Preserving Diffeomorphic Warping Process. In: Blanc-Talon, J., Helbert, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2018. Lecture Notes in Computer Science(), vol 11182. Springer, Cham. https://doi.org/10.1007/978-3-030-01449-0_44

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  • DOI: https://doi.org/10.1007/978-3-030-01449-0_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01448-3

  • Online ISBN: 978-3-030-01449-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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