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Multiple View 3D Reconstruction with Rolling Shutter Cameras

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 598))

Abstract

Nowadays Rolling shutter CMOS cameras are embedded on a lot of devices. This type of cameras does not have its retina exposed simultaneously but line by line. The resulting distortions affect structure from motion methods developed for global shutter, like CCD cameras. The bundle adjustment method presented in this paper deals with rolling shutter cameras. We use a projection model which considers pose and velocity and needs 6 more parameters for one view in comparison to the global shutter model. We propose a simplified model which only considers distortions due to rotational speed. We compare it to the global shutter model and the full rolling shutter one. The model does not need any condition on the inter-frame motion so it can be applied to fully independent views, even with global shutter images equivalent to a null velocity. We also propose a way to handle epipolar geometry for rolling shutter. It is shown that constraint using essential matrix becomes non linear, and we show how to use it to recover poses and speeds from matched points. Results with both synthetic and real images shows that the simplified model can be considered as a good compromise between a correct geometrical modelling of rolling shutter effects and the reduction of the number of extra parameters.

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Correspondence to Gaspard Duchamp .

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Duchamp, G., Ait-Aider, O., Royer, E., Lavest, JM. (2016). Multiple View 3D Reconstruction with Rolling Shutter Cameras. In: Braz, J., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2015. Communications in Computer and Information Science, vol 598. Springer, Cham. https://doi.org/10.1007/978-3-319-29971-6_12

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  • DOI: https://doi.org/10.1007/978-3-319-29971-6_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29970-9

  • Online ISBN: 978-3-319-29971-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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