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Image Mosaicing by Camera Pose Estimation Based on Extended Kalman Filter

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

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Abstract

We develop a sequential image mosaicing approach for aerial images of pseudo-planar scenes which is based on the estimation of camera pose from images. We use Extended Kalman Filter (EKF) to update the camera pose and scene parameters with every new image which improves the global consistency of the mosaic. Proposed approach is tested on aerial images where visually appealing results are obtained and residuals are quantified.

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Author information

Authors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey

    Alper Yildirim & Mustafa Unel

Authors
  1. Alper Yildirim
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  2. Mustafa Unel
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Corresponding author

Correspondence to Mustafa Unel .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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Yildirim, A., Unel, M. (2014). Image Mosaicing by Camera Pose Estimation Based on Extended Kalman Filter. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_49

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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