Excellent Computer Vision Paper Award by Google Research for 2012

Our paper

  • M. Grundmann, V. Kwatra, Daniel Castro, and I. Essa (2012), “Calibration-Free Rolling Shutter Removal,” in IEEE Conference on Computational Photography (ICCP), 2012. (Best Paper Award) [PDF] [WEBSITE] [VIDEO] [DOI] [BIBTEX]
    @InProceedings{ 2012-Grundmann-CRSR,
    author  = {Matthias Grundmann and Vivek Kwatra and Daniel
    Castro and Irfan Essa},
    awards  = {(Best Paper Award)},
    booktitle  = {{IEEE Conference on Computational Photography
    (ICCP)}},
    doi = {10.1109/ICCPhot.2012.6215213},
    pdf = {http://www.cc.gatech.edu/~irfan/p/2012-Grundmann-CRSR.pdf},
    publisher  = {IEEE Computer Society},
    title = {Calibration-Free Rolling Shutter Removal},
    url = {http://www.cc.gatech.edu/cpl/projects/rollingshutter/},
    video = {http://www.youtube.com/watch?v=_Pr_fpbAok8},
    year = {2012}
    }

was listed as one of the “Excellent Papers” by Google Research for 2012.

This time we honor the influential papers authored or co-authored by Googlers covering all of 2012 — covering roughly 6% of our total publications.  It’s tough choosing, so we may have left out some important papers.  So, do see the publications list to review the complete group.

Calibration-Free Rolling Shutter Removal

Matthias Grundmann*, Vivek Kwatra*, Daniel Castro, Irfan Essa*, International Conference on Computational Photography ’12. Best paper.

Mobile phones and current generation DSLR’s, contain an electronic rolling shutter, capturing each frame one row of pixels at a time. Consequently, if the camera moves during capture, it will cause image distortions ranging from shear to wobbly distortions. We propose a calibration-free solution based on a novel parametric mixture model to correct these rolling shutter distortions in videos that enables real-time rolling shutter rectification as part of YouTube’s video stabilizer.

https://ai.googleblog.com/2013/06/excellent-papers-for-2012.html

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