• DocumentCode
    154127
  • Title

    Motion aware motion invariance

  • Author

    McCloskey, Scott ; Muldoon, Kelly ; Venkatesha, Sharath

  • Author_Institution
    Honeywell ACS Labs., Golden Valley, MN, USA
  • fYear
    2014
  • fDate
    2-4 May 2014
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    We address motion de-blurring using a computational camera that captures an image while the stabilizing optical element moves in a modified Canon IS lens. Our work builds on that of Levin et al. [11], who introduce parabolic motion as a means of achieving invariance to unknown subject velocity in an a priori known direction. While the previous work addresses a specific scenario - exact knowledge of motion orientation and a uniform, symmetric prior on its magnitude - we generalize this to address scenarios where the motion of objects in the scene or the camera itself are known to various extents. We describe a motion invariant camera based on an off-the-shelf lens, and show how its motion and position sensors can be used to inform both the image capture and de-blurring. We demonstrate that our changes to motion invariance improve the quality of captured images in the case of both object and camera motion.
  • Keywords
    image capture; image motion analysis; image restoration; image sensors; photographic lenses; captured image quality improvement; computational camera; modified Canon IS lens; motion aware motion invariance; motion deblurring; motion invariant camera; motion sensor; object motion; off-the-shelf lens; optical element stabilisation; parabolic motion; position sensor; Acceleration; Cameras; ISO; Image sensors; Lenses; Noise; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Photography (ICCP), 2014 IEEE International Conference on
  • Conference_Location
    Santa Clara, CA
  • Type

    conf

  • DOI
    10.1109/ICCPHOT.2014.6831810
  • Filename
    6831810